The long coaxial inner magnetically insulated transmission line (MITL) is considered as a possible transmission line to guide power to deep underground high yield fusion experiments. The considered dimensions are of order 10-15 meters in length, 60 cm radius, and 6 mm AK gap, with peak current 60 MA and peak pulse 100 ns. In designing such a MITL, the main concern is power loss due to low density plasmas being produced by high electric fields and temperatures. It is found that a 10m-long prototypical MITL is a viable design, with maximum current losses below 10% and temperature rise due to electron impact not exceeding 400°C, thereby avoiding thermal desorption of contaminants and the formation of low density plasmas.
Existing standards and policies for interconnecting distributed energy resources (DERs) into low voltage spot networks severely limits the amount of DER installed on those networks to avoid negative impacts on protection systems. This report investigates options for upgrading the protection systems of spot networks to allow for additional DER installations beyond the normal limits (i.e., no reverse power flows allowed onto the MV system). Eight potential upgrade options are discussed that span various methods for new network protector algorithms, hardware upgrades, and the addition of communication. Each method has tradeoffs in terms of accuracy of detecting faults, requirements to upgrade equipment in the spot networks, need for communication, and sensitivity to false trips—all of which are explored in this report.
This file provides the documentation for several Python scripts that were developed by Sandia National Laboratories to enhance the automation and customization capabilities for performing various distribution system planning and analysis tasks in CYME. Specifically, these scripts (.py files detailed in Figure 1) enable the user to evaluate different distribution system configurations and the resulting impacts on hosting capacity results and other metrics. In general, these scripts—and the accompanying documentation—provide the foundation upon which future customized tools can be created. For example, the scripts show how to extract and modify parameters of various circuit components, set up and run analyses using built-in CYME tools (iteratively), and export reports for further evaluations and comparisons. Thus, the capabilities and syntaxes used in the scripts can be adapted and leveraged for countless other objectives.
Sandia National Laboratories has tested and evaluated the Reftek Wrangler digitizer. The Wrangler digitizers are intended to record sensor output for seismic and infrasound monitoring applications. The purpose of this digitizer evaluation is to measure the performance characteristics in such areas as power consumption, input impedance, sensitivity, full scale, self-noise, dynamic range, system noise, response, passband, and timing. The Wrangler digitizers are being evaluated for potential use in the International Monitoring System (IMS) and On-site Inspection (OSI) components of Comprehensive Nuclear-Test-Ban Treaty (CTBT).
Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency-based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep-learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short-time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. Here, we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN-based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground-truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real-world data shows that both the CNN and MWCNN models outperform standard band-pass filtering (BPF; average improvement in signal-to-noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.
Mitrani, James M.; Ampleford, David; Chandler, Gordon A.; Eckart, Mark J.; Hahn, Kelly D.; Jeet, Justin; Kerr, Shaun M.; Mannion, Owen; Moore, Alastair M.; Schlossberg, David J.; Youmans, Amanda E.; Grim, Gary P.
On pulsed fusion experiments, the neutron time of flight (nToF) diagnostic provides critical information on the fusion neutron energy spectrum. This work presents an analysis technique that uses two collinear nToF detectors, potentially to measure nuclear bang time and directional flow velocities. Two collinear detectors may be sufficient to disambiguate the contributions of nuclear bang time and directional flow velocities to the first moment of the neutron energy spectrum, providing an independent measurement of nuclear bang time. Preliminary results from measured nToF traces on the National Ignition Facility and additional applications of this technique are presented.
This report accompanies Sandia’s deflectometry tool, SOFAST 2.0, providing both a user guide and a basic technical description. SOFAST is a deflectometry tool used to measure surface slope maps of concentrating solar power (CSP) mirrors and collectors. The original SOFAST performed high-resolution measurement of a variety of CSP mirror types. SOFAST 2.0 is a completely new version, re-implemented in Python and including many extensions and improvements.
The motivation of this work was to complement other studies intended to enhance and update DOE-HDBK-3010-94 for hazard scenarios like nuclear waste fires. In this work, a uniquely designed combustion chamber was successfully integrated with a light scattering technique to characterize soot aggregates. The chamber design allowed for soot investigation within the flame as well as after soot left the incandescent flame region.
Interpenetrating lattices consist of two or more interwoven but physically separate sub-lattices with unique behaviors derived from their multi-body construction. If the sublattices are constructed or coated with an electrically conducting material, the close proximity and high surface area of the electrically isolated conductors allow the two lattices to interact electromagnetically either across the initial dielectric filled gap or through physical contact. Changes in the size of the dielectric gap between the sub-lattices induced by deformation can be measured via capacitance or resistance, allowing a structurally competent lattice to operate as a force or deformation sensor. In addition to resistive and capacitive deformation sensing, this work explores capacitance as a fundamental metamaterial property and the environmental sensing behaviors of interpenetrating lattices.
The process of training object detection (OD) or image segmentation model requires both a substantial amount of data and technical knowledge, which often creates challenges in applying these types of models to their full potential. In order to streamline the process of developing these models, we propose a new pipeline where a foundation model assists in the dataset generation. Then this resulting dataset is used to fine-tune a fast light-weight model to perform the custom segmentation or OD. This resulting model is also fit for real-time image segmentation, such as in a video stream.
Explosion sources have been observed to generate significant shear-wave energy despite their isotropic nature. To investigate this phenomenon, we conduct an analysis of the seismic data collected as part of the Source Physics Experiment (SPE): Dry Alluvium Geology (DAG) and investigate the generation of shear-wave energy via scattering. The data were produced by three underground chemical explosions and consist of three-component seis-mograms, which were recorded by the DAG Large-N array. Synthetic tests suggest that for the DAG experiments, small-scale stochastic heterogeneities, defined as features with correlation lengths of 10–100s of meters, are more effective than large-scale geologic structure (scales >1–10 km) at reproducing the scattering of explosion generated wavefields observed at DAG. We analyze the seismic data for spatially variable ratios between transversely and radially polarized seismic energy, and then estimate the mean free path of P and S waves. All analyses are conducted within a frequency band of 5–50 Hz. The ratio of transversely to radially polarized energy is the highest in the east and west portion of the Large-N array. In addition, the magnitude of the estimated S-wave mean free path is shorter in the eastern portion of the Large-N array. This variation indicates that the eastern area of the DAG array is where more scattering is occurring, suggesting azimuthal dependence of P-to-P and P-to-S scattering. This azimuthal dependence of P-to-S scattering can have implications for explosion discrimination based on spectral ratios of seismic wave types, because the general assumption is that explosions do not generate shear-wave energy. Synthetic tests modeling only larger-scale geologic structure had lower transversely polarized energy (only four stations showing a transversely to radially polarized energy ratio greater than 1) and fewer stations (<10) displaying shorter (<300 m) mean free paths than what was observed in the DAG data results.
The critical stress for cutting of a void and He bubble (generically referred to as a cavity) by edge and screw dislocations has been determined for FCC Fe0.70Cr0.20Ni0.10—close to 300-series stainless steel—over a range of cavity spacings, diameters, pressures, and glide plane positions. The results exhibit anomalous trends with spacing, diameter, and pressure when compared with classical theories for obstacle hardening. These anomalies are attributed to elastic anisotropy and the wide extended dislocation core in low stacking fault energy metals, indicating that caution must be exercised when using perfect dislocations in isotropic solids to study void and bubble hardening. In many simulations with screw dislocations, cross-slip was observed at the void/bubble surface, leading to an additional contribution to strengthening. We refer to this phenomenon as cavity cross-slip locking, and argue that it may be an important contributor to void and bubble hardening.
Hydrogen powered locomotives are being explored to reduce emissions in rail applications. The risks of operations like refueling should be understood to ensure safe environments for workers and members of the public. Sensitivity analyses were conducted using HyRAM+ to identify major drivers of risk and compare effects of system parameters on individual risk. The consequences of jet fires from full-bore leaks dominated the risk, compared to explosions or smaller leaks. Pipe size, leak detection capability, and leak frequencies of system components greatly affected risk while overpressure modeling parameters and ambient conditions had little effect. The effects of personal protective equipment (PPE) materials on individual risk were quantified by reducing the individual’s exposure time or absorbed thermal dose. PPE only showed a risk reduction in low-risk cases. This study highlighted target areas for risk mitigation, including leak detection equipment and component maintenance, and indicated that the minimal effects of other parameters on risk may not justify prescriptive requirements for refueling operators.
The formation of magnesium chloride-hydroxide salts (magnesium hydroxychlorides) has implications for many geochemical processes and technical applications. For this reason, a thermodynamic database for evaluating the Mg(OH)2–MgCl2–H2O ternary system from 0 °C–120 °C has been developed based on extensive experimental solubility data. Internally consistent sets of standard thermodynamic parameters (ΔGf°, ΔHf°, S°, and CP) were derived for several solid phases: 3 Mg(OH)2:MgCl2:8H2O, 9 Mg(OH)2:MgCl2:4H2O, 2 Mg(OH)2:MgCl2:4H2O, 2 Mg(OH)2:MgCl2: 2H2O(s), brucite (Mg(OH)2), bischofite (MgCl2:6H2O), and MgCl2:4H2O. First, estimated values for the thermodynamic parameters were derived using a component addition method. These parameters were combined with standard thermodynamic data for Mg2+(aq) consistent with CODATA (Cox et al., 1989) to generate temperature-dependent Gibbs energies for the dissolution reactions of the solid phases. These data, in combination with values for MgOH+(aq) updated to be consistent with Mg2+-CODATA, were used to compute equilibrium constants and incorporated into a Pitzer thermodynamic database for concentrated electrolyte solutions. Phase solubility diagrams were constructed as a function of temperature and magnesium chloride concentration for comparisons with available experimental data. To improve the fits to the experimental data, reaction equilibrium constants for the Mg-bearing mineral phases, the binary Pitzer parameters for the MgOH+ — Cl− interaction, and the temperature-dependent coefficients for those Pitzer parameters were constrained by experimental phase boundaries and to match phase solubilities. These parameter adjustments resulted in an updated set of standard thermodynamic data and associated temperature-dependent functions. The resulting database has direct applications to investigations of magnesia cement formation and leaching, chemical barrier interactions related to disposition of heat-generating nuclear waste, and evaluation of magnesium-rich salt and brine stabilities at elevated temperatures.
Typical QRAs provide deterministic estimates and understanding of risks posed but are constructed using significant assumptions and uncertainties due to limited data availability and historical momentum of using nominal estimates. This report presents a hydrogen QRA analysis using HyRAM+ that incorporates uncertainty with Latin hypercube sampling and sensitivity analysis using linear regression.
Concentrating solar mirrors need to have correct geometry to accurately focus sunlight onto a receiver. SOFAST is a tool created at Sandia National Laboratories which measures a mirror’s surface normal at a dense sampling of points, enabling evaluation of a given mirror’s expected performance. SOFAST supports general mirrors, including concentrating solar heliostats, troughs, and dishes. The examples presented in this report predominantly focus on heliostats.
Experiments on the SPHINX accelerator at Sandia National Laboratories (SNL) looked at electron beam heating of metal foils used in Bremsstrahlung flash x-ray production. Titanium and tantalum foils were exposed to electron beam energies of up to 2MeV to determine surface heating. As part of the experiment, the x-ray dose profiles were characterized using a scintillating panel (EJ-230) placed both perpendicular and parallel to the photon beam. This was followed by direct electron beam imaging using a fast-gated ICCD camera and a fused silica Cherenkov witness plate. Once characterized, the foil was directly measured using a mid-wave (3-5 micron) infrared camera (MWIR) to determine the peak surface temperatures and spatially-resolved thermal profiles. Additionally, an IR pyrometer was used in a single wavelength mode (2.3 µm) to determine localized surface temperatures as well. Results are compared with calculations of surface temperatures obtained from e-beam energy depositions combined with the specific heats of the foils. This is the first attempt to directly measure the surface temperature profile on a short-pulse (10 nanoseconds) flash x-ray source using MWIR imaging. These data are directly relevant for Monte Carlo/Integrated Tiger Series electron/photon transport code results being used in the design of future Bremsstrahlung sources such as CREST.
This report provides instructions on how to perform an OpenCSP camera lens calibration, which characterizes the inherent distortion in camera-lens systems. This calibration is necessary for many OpenCSP photogrammetry calculations and should be performed individually for every new camera or after adjusting lens settings.
Harrison, Lindsay M.; Clark, Alisha N.; Sarafian, Adam R.; Davis, Jean-Paul; Jacobsen, Steven D.; Townsend, Joshua P.; Nie, Craig D.; Moore, Lisa A.; Mckenzie, Matthew E.; Tingley, James E.; Moore, Galan G.; Youngman, Randall E.
Main content extraction is a method to isolate the relevant content from a webpage and remove extraneous content such as advertisements and sidebars. There are many different Python and Java libraries that attempt to perform main content extraction through various algorithms. Due to the differing structures between web pages, there is no “perfect” way to accomplish this task, motivating an evaluation of different main content extraction libraries.
The slides will be presented at a DOE CESER Peer Review for the Risk Management Tools and Technology (RMT) that provide an overview of the CAPSec project. The slides discuss the live-updates and live-migration results along with an overview of the demonstration performed for this project. The peer review is scheduled for August 27-29.
The goal of this project is to investigate the molecular interactions of H2 with earth materials (EMs) that may potentially affect economics and safety of H2 geological storage (HGS). We investigated (1) the H2 intercalation into interlayers of phyllosilicates, (2) the competitive adsorption of H2/CH4 onto porous materials, and (3) solubility of H2 in interfacial and confined hydrocarbons. Our results indicate that (i) H2 intercalation into hydrated interlayers is thermodynamically unfavorable and H2 solubility in hydrated clay interlayers is in the same order of magnitude as that in bulk water, (ii) CH4 outcompetes H2 in adsorption onto kerogen, due to stronger CH4-kerogen interactions than H2-kerogen interactions, (iii) H2 tends to dissolve more in oil than in water, and the introduction of CO2 as a cushion gas reduces H2 partitioning near the kaolinite surfaces. The outcomes provide foundational knowledge for preparing the USA for future storage site selection and storage system design, supporting DOE missions in clean and secured energy.
Bays, Nathan R.; Davis, Jacob; Tom, Nathan; Thiagarajan, Krish
This study presents theoretical formulations to evaluate the fundamental parameters and performance characteristics of a bottom-raised oscillating surge wave energy converter (OSWEC) device. Employing a flat plate assumption and potential flow formulation in elliptical coordinates, closed-form equations for the added mass, radiation damping, and excitation forces/torques in the relevant pitch-pitch and surge-pitch directions of motion are developed and used to calculate the system's response amplitude operator and the forces and moments acting on the foundation. The model is benchmarked against numerical simulations using WAMIT and WEC-Sim, showcasing excellent agreement. The sensitivity of plate thickness on the analytical hydrodynamic solutions is investigated over several thickness-to-width ratios ranging from 1:80 to 1:10. The results show that as the thickness of the benchmark OSWEC increases, the deviation of the analytical hydrodynamic coefficients from the numerical solutions grows from 3 % to 25 %. Differences in the excitation forces and torques, however, are contained within 12 %. While the flat plate assumption is a limitation of the proposed analytical model, the error is within a reasonable margin for use in the design space exploration phase before a higher-fidelity (and thus more computationally expensive) model is employed. A parametric study demonstrates the ability of the analytical model to quickly sweep over a domain of OSWEC dimensions, illustrating the analytical model's utility in the early phases of design.
To extend NUREG-1465 and high burnup fuel source term (SAND2023-01313) recommendations, representative radiological releases to containment – patterned after NUREG-1465 – have been evaluated for LWRs utilizing iron-chromium-aluminum (FeCrAl) alloys in place of zirconium-based alloys in major core structures (cladding and fuel canisters) and high burnup fuel with enrichments of 8% and 10% for PWRs and BWRs, respectively. Representative radionuclide releases are generated for this accident tolerant fuel concept by applying non-parametric bootstrap methods to MELCOR simulation results. Accident scenarios considered in this analysis include principle contributors to historical core damage frequency estimates for a range of nuclear reactor technologies representative of the operating U.S.A. fleet of nuclear reactors.
The rise of grid modernization has been prompted by the escalating demand for power, the deteriorating state of infrastructure, and the growing concern regarding the reliability of electric utilities. The smart grid encompasses recent advancements in electronics, technology, telecommunications, and computer capabilities. Smart grid telecommunication frameworks provide bidirectional communication to facilitate grid operations. Software-defined networking (SDN) is a proposed approach for monitoring and regulating telecommunication networks, which allows for enhanced visibility, control, and security in smart grid systems. Nevertheless, the integration of telecommunications infrastructure exposes smart grid networks to potential cyberattacks. Unauthorized individuals may exploit unauthorized access to intercept communications, introduce fabricated data into system measurements, overwhelm communication channels with false data packets, or attack centralized controllers to disable network control. An ongoing, thorough examination of cyber attacks and protection strategies for smart grid networks is essential due to the ever-changing nature of these threats. Previous surveys on smart grid security lack modern methodologies and, to the best of our knowledge, most, if not all, focus on only one sort of attack or protection. This survey examines the most recent security techniques, simultaneous multi-pronged cyber attacks, and defense utilities in order to address the challenges of future SDN smart grid research. The objective is to identify future research requirements, describe the existing security challenges, and highlight emerging threats and their potential impact on the deployment of software-defined smart grid (SD-SG).
The rotating bending fatigue (RBF) behavior (fully reversed, R = −1) of additively manufactured (AM) Ti–6Al–4V alloy produced via laser powder bed fusion (PBF-L) was investigated with respect to different microstructures achieved through novel heat treatments. The investigation herein seeks to elucidate the effect of microstructure by controlling variables that can affect fatigue behavior in Ti–6Al–4V, such as chemistry, porosity, and surface roughness. In order to control these variables, different hot isostatic pressing (HIP) treatments at 800 °C, 920 °C, and 1050 °C with a 920 °C temper were applied to three sets of Ti–6Al–4V cylinders that originated from the same PBF-L build, such that there were 30 tests per condition. After HIP treatment, the specimens were machined and tested. The highest runout stress was achieved after sub-β transus HIP at 800 °C for 2 h at 200 MPa of pressure. A significant drop in fatigue strength was attributed to large prior-β grains and grain boundary α resulting from super-β transus HIP treated specimens. For the sub-β transus HIP specimens, differences in fatigue strength were attributed to α lath thickness, relative dislocation density, and dislocation boundary strengthening.
Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.
A series of tension and compression tests were performed on typical transfer tubes made of 304L corrosion-resistant steel. The results were compiled and converted to true stress and true plastic strain for comparison to numerical models. The parameters of a Johnson-Cook constitutive model and fracture criterion were calibrated to mimic the test data. Comparisons were made between the converted data and the empirical formulas in the Johnson-Cook model. Simulations were performed to evaluate the implementation of the formula in finite element analysis, and the parameters were adjusted to improve the correlation.
In this document I will discuss different implementations of Covariance Intersection (CI) for object triangulation as well as the robustness of CI. For CI methods we will compare the performance of different methods and discuss edge cases which must be considered. For robustness we will focus on the impact of removing sensors on the final fused estimate. Here we look at factors which influence the final fused covariance matrix.
The slides will be presented at a DOE CESER Peer Review for the Risk Management Tools and Technology (RMT) that provide an overview of the sDERC project. The slides discuss the project plan for this new project and how the results will be demonstrated at the conclusion of this project. The peer review is scheduled for August 27-29.
Leaks in a hydrogen system can have destructive effects on other components within the system, leading to cascading leaks. The risk of cascading leaks is not currently quantified in many existing risk frameworks, but the prevalence of cascading failures in historical hydrogen facility accidents necessitates further study. A method for quantifying the probability, frequency, and risk of cascaded leaks is proposed. The method provides example scenarios of metrics that would set off cascading failures from each physical effect, including a jet fire melting the O-ring of another component, and an overpressure event from an initial explosion shearing off another component from the system. Cascading leak frequencies and individual risk are calculated for an example hypothetical system. While cascading leaks are quantitatively demonstrated to add to the overall risk, their contributions are small and may not add value to a risk assessment when analyzed in this rigorous quantitative framework.
To extend NUREG-1465 and high burnup fuel source term (SAND2023-01313) recommendations, representative radiological releases to containment – patterned after NUREG-1465 – have been evaluated for LWRs utilizing the chromium-coating on major zircaloy structures (cladding and fuel canisters) and high burnup fuel with enrichments of 8% and 10% for PWRs and BWRs, respectively. Representative radionuclide releases are generated for this accident tolerant fuel concept by applying non-parametric bootstrap methods to MELCOR simulation results. Accident scenarios considered in this analysis include principle contributors to historical core damage frequency estimates for a range of nuclear reactor technologies representative of the operating U.S.A. fleet of nuclear reactors.
Cybersecurity certification programs for Electric Vehicle Supply Equipment (EVSE) are fragmented due to no single certification covering all aspects of the device and additionally the existence of multiple programs and under different levels of regulation. These devices are also confronted by the intricate assembly of product software, firmware, and hardware. Devices contain both logical and physical interfaces. These multifaceted devices have vulnerabilities at many levels and interconnect with other potentially vulnerable systems including the electric vehicle, the cloud where data and payment information are stored, and the electric grid and electric grid equipment including utilities. Of the EVSE certification programs that are found, none are directly for the cybersecurity of EVSE. Many standards are for safety, specifically battery safety, some are cybersecurity standards for other types of equipment and can be modeled for EVSE. In specific, ISA/IEC 62443 is found to be significantly in line with EVSE security needs and will be used in future testing to certify EVSE and help guide the project to demonstrate where gaps exist, where strengths lie in the standard and how this can be used to lead the certification efforts in harmonizing EVSE cybersecurity standards. In addition, there are multiple efforts that are currently seeking to build EVSE standards or revise existing standards to address gaps. This effort is seeking to establish a cybersecurity program for EVSE that will inform customers and help increase the level of security across products and state EVSE procurements to achieve consistency across different jurisdictions.
We have attempted to capture a sense of the scientific state of the art in studying social media platforms, including data collection from platforms, understanding platform behavior, known adversarial uses, and adverse content detection, classification, and quantification. Our coverage of the field is backed up by roughly two hundred citations, and it concludes with a comparative analysis and a list of apparent gaps and potential paths forward.
The slides will be presented at a DOE CESER Peer Review for the Risk Management Tools and Technology (RMT) that provide an overview of the ESSec project. The slides discuss the containerization and orchestration tools for energy storage systems and our results along with an overview of the demonstration performed for this project. The peer review is scheduled for August 27-29.
In recent years, microalgae have been identified as potential source of biofuel due to their ability to grow abundantly in little time. As photosynthetic organisms, microalgae only need water, light, micronutrients, and carbon dioxide to yield algal biomass. Several applications for this biomass are being studied, such as the extraction of biofuel (Zhang et al. 2022) as well as wastewater treatment (Rude et al. 2022). Two specific microalgae species have been identified as uniquely prolific: Picochlorum celeri, a saltwater species, and Chlorella sorokiniana 1116, a freshwater species. Both species showcased survival in less-than-ideal conditions and showcased hardiness in their respective waters (Krishnan et al. 2021), making them popular specimen to be studied for a variety of applications. This project involved two components, the first component focusing on the development of a growth curve for P. celeri and the second studying varying salt concentration in both species.
This document provides a technical description of algorithms used in the OpenCSP code repository that are common to deflectometry. This document is meant to be a technical reference that describes the internal algorithms of OpenCSP. An example program that uses these algorithms is SOFAST 2.0 [1].
Climate and sea level change is causing numerous challenges across the globe to human societies and the cultural and infrastructure investments they have made over hundreds of years based on previous modalities in climate and sea level. Decarbonizing our global economy is therefore essential to stopping additional emissions of CO2 to the atmosphere. One proposed decarbonization technology that has been advanced as a replacement for the “hydrocarbon economy” that exists today is the “hydrogen economy.” In the hydrogen economy, hydrogen is both an energy carrier and an industrial feedstock that can replace hydrocarbons’ traditional roles in these systems. While most hydrogen is produced from conventional, fossil-based feedstocks, hydrogen comes with the added benefits of being able to be made from water and electricity providing a promising way to store renewable energy from wind and solar developments.
Study of subcooled pool boiling experiments performed using a dielectric coolant to test effects of variations in heater surface configuration on pool boiling characteristics.
Nuclear power plant (NPP) risk assessment is broadly separated into disciplines of nuclear safety, security, and safeguards. Different analysis methods and computer models have been constructed to analyze each of these as separate disciplines. However, due to the complexity of NPP systems, there are risks that can span all these disciplines and require consideration of safety-security (2S) interactions which allows a more complete understanding of the relationship among these risks. A novel leading simulator/trailing simulator (LS/TS) method is introduced to integrate multiple generic safety and security computer models into a single, holistic 2S analysis. A case study is performed using this novel method to determine its effectiveness. The case study shows that the LS/TS method avoided introducing errors in simulation, compared to the same scenario performed without the LS/TS method. A second case study is then used to illustrate an integrated 2S analysis which shows that different levels of damage to vital equipment from sabotage at a NPP can affect accident evolution by several hours.
In magnetized liner inertial fusion (MagLIF), a cylindrical liner filled with fusion fuel is imploded with the goal of producing a one-dimensional plasma column at thermonuclear conditions. However, structures attributed to three-dimensional effects are observed in self-emission x-ray images. Despite this, the impact of many experimental inputs on the column morphology has not been characterized. We demonstrate the use of a linear regression analysis to explore correlations between morphology and a wide variety of experimental inputs across 57 MagLIF experiments. Results indicate the possibility of several unexplored effects. For example, we demonstrate that increasing the initial magnetic field correlates with improved stability. Although intuitively expected, this has never been quantitatively assessed in integrated MagLIF experiments. We also demonstrate that azimuthal drive asymmetries resulting from the geometry of the “current return can” appear to measurably impact the morphology. In conjunction with several counterintuitive null results, we expect the observed correlations will encourage further experimental, theoretical, and simulation-based studies. Finally, we note that the method used in this work is general and may be applied to explore not only correlations between input conditions and morphology but also with other experimentally measured quantities.
This a presentation for the 2024 Signal Processing Applied to Nonproliferation (SPAN) 2024 workshop. It discusses seismic research conducted at the Redmond Mine as part of the NA-22 STILGAR project.
These instructions show how to use the OpenCSP Scene Reconstruction application. Scene Reconstruction calculates the three-dimensional positions of Aruco markers placed around a scene using photogrammetry. This has multiple applications within OpenCSP; this document is referenced by multiple other OpenCSP documents.
The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol injection, have been proposed as mitigation strategies, but the downstream effects of such actions on a complex climate system are not well understood. The development of algorithmic techniques for quantifying relationships between source and impact variables related to a climate event (i.e., a climate pathway) would help inform policy decisions. Data-driven deep learning models have become powerful tools for modeling highly nonlinear relationships and may provide a route to characterize climate variable relationships. In this paper, we explore the use of an echo state network (ESN) for characterizing climate pathways. ESNs are a computationally efficient neural network variation designed for temporal data, and recent work proposes ESNs as a useful tool for forecasting spatiotemporal climate data. However, ESNs are noninterpretable black-box models along with other neural networks. The lack of model transparency poses a hurdle for understanding variable relationships. We address this issue by developing feature importance methods for ESNs in the context of spatiotemporal data to quantify variable relationships captured by the model. We conduct a simulation study to assess and compare the feature importance techniques, and we demonstrate the approach on reanalysis climate data. In the climate application, we consider a time period that includes the 1991 volcanic eruption of Mount Pinatubo. This event was a significant stratospheric aerosol injection, which acts as a proxy for an anthropogenic stratospheric aerosol injection. We are able to use the proposed approach to characterize relationships between pathway variables associated with this event that agree with relationships previously identified by climate scientists.
