Publications

The interplay between hydrogen and dislocations (e.g., core and elastic energies, and dislocation–dislocation interactions) has implications on hydrogen embrittlement but is poorly understood. Continuum models of hydrogen enhanced local plasticity have not considered the effect of hydrogen on dislocation core energies. Energy minimization atomistic simulations can only resolve dislocation core energies in hydrogen-free systems because hydrogen motion is omitted so hydrogen atmosphere formation can’t occur. Additionally, previous studies focused more on face-centered-cubic than body-centered-cubic metals. Discrete dislocation dynamics studies of hydrogen–dislocation interactions assume isotropic elasticity, but the validity of this assumption isn’t understood. Here, we perform time-averaged molecular dynamics simulations to study the effect of hydrogen on dislocation energies in body-centered-cubic iron for several dislocation character angles. We see atmosphere formation and highly converged dislocation energies. We find that hydrogen reduces dislocation core energies but can increase or decrease elastic energies of isolated dislocations and dislocation–dislocation interaction energies depending on character angle. We also find that isotropic elasticity can be well fitted to dislocation energies obtained from simulations if the isotropic elastic constants are not constrained to their anisotropic counterparts. These results are relevant to ongoing efforts in understanding hydrogen embrittlement and provide a foundation for future work in this field.

In this work, we investigate the potential of liquid hydrogen storage (LH₂) on-board Class-8 heavy duty trucks to resolve many of the range, weight, volume, refueling time and cost issues associated with 350 or 700-bar compressed H₂ storage in Type-3 or Type-4 composite tanks. We present and discuss conceptual storage system configurations capable of supplying H₂ to fuel cells at 5-bar with or without on-board LH₂ pumps. Structural aspects of storing LH₂ in double walled, vacuum insulated, and low-pressure Type-1 tanks are investigated. Structural materials and insulation methods are discussed for service at cryogenic temperatures and mitigation of heat leak to prevent LH₂ boiloff. Failure modes of the liner and shell are identified and analyzed using the regulatory codes and detailed finite element (FE) methods. The conceptual systems are subjected to a Failure modes and effects analysis (FMEA) and a safety, codes, and standards (SCS) review to rank failures and identify safety gaps. The results indicate that the conceptual systems can reach 19.6% usable gravimetric capacity, 40.9 g-H₂/L usable volumetric capacity and $174-183/kg-H₂ cost (2016 USD) when manufactured 100,000 systems annually.

Spent nuclear fuel repository simulations are currently not able to incorporate detailed fuel matrix degradation (FMD) process models due to their computational cost, especially when large numbers of waste packages breach. The current paper uses machine learning to develop artificial neural network and k-nearest neighbor regression surrogate models that approximate the detailed FMD process model while being computationally much faster to evaluate. Using fuel cask temperature, dose rate, and the environmental concentrations of CO32−, O2, Fe2+, and H2 as inputs, these surrogates show good agreement with the FMD process model predictions of the UO2 degradation rate for conditions within the range of the training data. A demonstration in a full-scale shale repository reference case simulation shows that the incorporation of the surrogate models captures local and temporal environmental effects on fuel degradation rates while retaining good computational efficiency.

When exposed to mechanical environments such as shock and vibration, electrical connections may experience increased levels of contact resistance associated with the physical characteristics of the electrical interface. A phenomenon known as electrical chatter occurs when these vibrations are large enough to interrupt the electric signals. It is critical to understand the root causes behind these events because electrical chatter may result in unexpected performance or failure of the system. The root causes span a variety of fields, such as structural dynamics, contact mechanics, and tribology. Therefore, a wide range of analyses are required to fully explore the physical phenomenon. This paper intends to provide a better understanding of the relationship between structural dynamics and electrical chatter events. Specifically, electrical contact assembly composed of a cylindrical pin and bifurcated structure were studied using high fidelity simulations. Structural dynamic simulations will be performed with both linear and nonlinear reduced-order models (ROM) to replicate the relevant structural dynamics. Subsequent multi-physics simulations will be discussed to relate the contact mechanics associated with the dynamic interactions between the pin and receptacle to the chatter. Each simulation method was parametrized by data from a variety of dynamic experiments. Both structural dynamics and electrical continuity were observed in both the simulation and experimental approaches, so that the relationship between the two can be established.

The DevOps movement, which aims to accelerate the continuous delivery of high-quality software, has taken a leading role in reshaping the software industry. Likewise, there is growing interest in applying DevOps tools and practices in the domains of computational science and engineering (CSE) to meet the ever-growing demand for scalable simulation and analysis. Translating insights from industry to research computing, however, remains an ongoing challenge; DevOps for science and engineering demands adaptation and innovation in those tools and practices. There is a need to better understand the challenges faced by DevOps practitioners in CSE contexts in bridging this divide. To that end, we conducted a participatory action research study to collect and analyze the experiences of DevOps practitioners at a major US national laboratory through the use of storytelling techniques. We share lessons learned and present opportunities for future investigation into DevOps practice in the CSE domain.

A method is presented to detect clear-sky periods for plane-of-array, time-averaged irradiance data that is based on the algorithm originally described by Reno and Hansen. We show this new method improves the state-of-the-art by providing accurate detection at longer data intervals, and by detecting clear periods in plane-of-array data, which is novel. We illustrate how accurate determination of clear-sky conditions helps to eliminate data noise and bias in the assessment of long-term performance of PV plants.

We present the SEU sensitivity and SEL results from proton and heavy ion testing performed on NVIDIA Xavier NX and AMD Ryzen V1605B GPU devices in both static and dynamic operation.

Laser-induced photoemission of electrons offers opportunities to trigger and control plasmas and discharges [1]. However, the underlying mechanisms are not sufficiently characterized to be fully utilized [2]. We present an investigation to characterize the effects of photoemission on plasma breakdown for different reduced electric fields, laser intensities, and photon energies. We perform Townsend breakdown experiments assisted by high-speed imaging and employ a quantum model of photoemission along with a 0D discharge model [3], [4] to interpret the experimental measurements.

Complex angle theory can offer new fundamental insights into refraction at the absorptive interface. In this work we propose a new method to induce isofrequency opening via addition of scattering in the dual interface system.

Machining-based deformation processing is used to produce metal foil and flat wire (strip) with suitable properties and quality for electrical power and renewable energy applications. In contrast to conventional multistage rolling, the strip is produced in a single-step and with much less process energy. Examples are presented from metal systems of varied workability, and strip product scale in terms of size and production rate. By utilizing the large-strain deformation intrinsic to cutting, bulk strip with ultrafine-grained microstructure, and crystallographic shear-texture favourable for formability, are achieved. Implications for production of commercial strip for electric motor applications and battery electrodes are discussed.

Due to their increased levels of reliability, meshed low-voltage (LV) grid and spot networks are common topologies for supplying power to dense urban areas and critical customers. Protection schemes for LV networks often use highly sensitive reverse current trip settings to detect faults in the medium-voltage system. As a result, interconnecting even low levels of distributed energy resources (DERs) can impact the reliability of the protection system and cause nuisance tripping. This work analyzes the possibility of modifying the reverse current relay trip settings to increase the DER hosting capacity of LV networks without impacting fault detection performance. The results suggest that adjusting relay settings can significantly increase DER hosting capacity on LV networks without adverse effects, and that existing guidance on connecting DERs to secondary networks, such as that contained in IEEE Std 1547-2018, could potentially be modified to allow higher DER deployment levels.

Modern Industrial Control Systems (ICS) attacks evade existing tools by using knowledge of ICS processes to blend their activities with benign Supervisory Control and Data Acquisition (SCADA) operation, causing physical world damages. We present Scaphy to detect ICS attacks in SCADA by leveraging the unique execution phases of SCADA to identify the limited set of legitimate behaviors to control the physical world in different phases, which differentiates from attacker's activities. For example, it is typical for SCADA to setup ICS device objects during initialization, but anomalous during process-control. To extract unique behaviors of SCADA execution phases, Scaphy first leverages open ICS conventions to generate a novel physical process dependency and impact graph (PDIG) to identify disruptive physical states. Scaphy then uses PDIG to inform a physical process-aware dynamic analysis, whereby code paths of SCADA process-control execution is induced to reveal API call behaviors unique to legitimate process-control phases. Using this established behavior, Scaphy selectively monitors attacker's physical world-targeted activities that violates legitimate process-control behaviors. We evaluated Scaphy at a U.S. national lab ICS testbed environment. Using diverse ICS deployment scenarios and attacks across 4 ICS industries, Scaphy achieved 95% accuracy & 3.5% false positives (FP), compared to 47.5% accuracy and 25% FP of existing work. We analyze Scaphy's resilience to futuristic attacks where attacker knows our approach.

The Information Harm Triangle (IHT) is a novel approach that aims to adapt intuitive engineering concepts to simplify defense in depth for instrumentation and control (I&C) systems at nuclear power plants. This approach combines digital harm, real-world harm, and unsafe control actions (UCAs) into a single graph named “Information Harm Triangle.” The IHT is based on the postulation that the consequences of cyberattacks targeting I&C systems can be expressed in terms of two orthogonal components: a component representing the magnitude of data harm (DH) (i.e., digital information harm) and a component representing physical information harm (PIH) (i.e., real-world harm, e.g., an inadvertent plant trip). The magnitude of the severity of the physical consequence is the aspect of risk that is of concern. The sum of these two components represents the total information harm. The IHT intuitively informs risk-informed cybersecurity strategies that employ independent measures that either act to prevent, reduce, or mitigate DH or PIH. Another aspect of the IHT is that the DH can result in cyber-initiated UCAs that result in severe physical consequences. The orthogonality of DH and PIH provides insights into designing effective defense in depth. The IHT can also represent cyberattacks that have the potential to impede, evade, or compromise countermeasures from taking appropriate action to reduce, stop, or mitigate the harm caused by such UCAs. Cyber-initiated UCAs transform DH to PIH.

The design of thermal protection systems (TPS), including heat shields for reentry vehicles, rely more and more on computational simulation tools for design optimization and uncertainty quantification. Since high-fidelity simulations are computationally expensive for full vehicle geometries, analysts primarily use reduced-physics models instead. Recent work has shown that projection-based reduced-order models (ROMs) can provide accurate approximations of high-fidelity models at a lower computational cost. ROMs are preferable to alternative approximation approaches for high-consequence applications due to the presence of rigorous error bounds. The following paper extends our previous work on projection-based ROMs for ablative TPS by considering hyperreduction methods which yield further reductions in computational cost and demonstrating the approach for simulations of a three-dimensional flight vehicle. We compare the accuracy and potential performance of several different hyperreduction methods and mesh sampling strategies. This paper shows that with the correct implementation, hyperreduction can make ROMs up to 1-3 orders of magnitude faster than the full order model by evaluating the residual at only a small fraction of the mesh nodes.

The V31 containment vessel was procured by the US Army Recovered Chemical Material Directorate (RCMD) as a third-generation EDS containment vessel. It is the fifth EDS vessel to be fabricated under Code Case 2564 of the 2019 ASME Boiler and Pressure Vessel Code, which provides rules for the design of impulsively loaded vessels. The explosive rating for the vessel, based on the code case, is 24 lb (11 kg) TNT-equivalent for up to 1092 detonations. This report documents the results of explosive tests that were performed on the vessel at Sandia National Laboratories in Albuquerque, New Mexico to qualify the vessel for field operations use. There were three design basis configurations for qualification testing. Qualification test (1) consisted of a simulated M55 rocket motor and warhead assembly of 24 lb (11 kg) of Composition C-4 (30 lb [14 kg] TNT equivalent). This test was considered the maximum load case, based on modeling and simulation methods performed by Sandia prior to the vessel design phase. Qualification test (2) consisted of a regular, right circular cylinder, unitary charge, located central to the vessel interior of 19.2 lb (8.72 kg) of Composition C-4 (24 lb [11 kg] TNT equivalent). Qualification test (3) consisted of a 12-pack of regular, right circular cylinders of 2 lb (908 g) each, distributed evenly inside the vessel (totaling 19.2 lb [8.72 kg] of C-4, or 24 lb [11 kg] TNT equivalent). All vessel acceptance criteria were met.

A quantum-cascade-laser-absorption-spectroscopy (QCLAS) diagnostic was used to characterize post-detonation fireballs of RP-80 detonators via measurements of temperature, pressure, and CO column pressure at a repetition rate of 1 MHz. Scanned-wavelength direct-absorption spectroscopy was used to measure CO absorbance spectra near 2008.5 cm−1 which are dominated by the P(0,31), P(2,20), and P(3,14) transitions. Line-of-sight (LOS) measurements were acquired 51 and 91 mm above the detonator surface. Three strategies were employed to facilitate interpretation of the LAS measurements in this highly nonuniform environment and to evaluate the accuracy of four post-detonation fireball models: (1) High-energy transitions were used to deliberately bias the measurements to the high-temperature outer shell, (2) a novel dual-zone absorption model was used to extract temperature, pressure, and CO measurements in two distinct regions of the fireball at times where pressure variations along the LOS were pronounced, and (3) the LAS measurements were compared with synthetic LAS measurements produced using the simulated distributions of temperature, pressure, and gas composition predicted by reactive CFD modeling. The results indicate that the QCLAS diagnostic provides high-fidelity data for evaluating post-detonation fireball models, and that assumptions regarding thermochemical equilibrium and carbon freeze-out during expansion of detonation gases have a large impact on the predicted chemical composition of the fireball.

Phosphor thermometry has become an established remote sensing technique for acquiring the temperature of surfaces and gas-phase flows. Often, phosphors are excited by a light source (typically emitting in the UV region), and their temperature-sensitive emission is captured. Temperature can be inferred from shifts in the emission spectra or the radiative decay lifetime during relaxation. While recent work has shown that the emission of several phosphors remains thermographic during x-ray excitation, the radiative decay lifetime was not investigated. The focus of the present study is to characterize the lifetime decay of the phosphor Gd2O2S:Tb for temperature sensitivity after excitation from a pulsed x-ray source. These results are compared to the lifetime decays found for this phosphor when excited using a pulsed UV laser. Results show that the lifetime of this phosphor exhibits comparable sensitivity to temperature between both excitation sources for a temperature range between 21 °C to 140 °C in increments of 20 °C. This work introduces a novel method of thermometry for researchers to implement when employing x-rays for diagnostics.

Here we examine models for particle curtain dispersion using drag based formalisms and their connection to streamwise pressure difference closures. Focusing on drag models, we specifically demonstrate that scaling arguments developed in DeMauro et. al. [1] using early time drag modeling can be extended to include late time particle curtain dispersion behavior by weighting the dynamic portion of the drag relative velocity e.g. (Formula Presented) by the inverse of the particle volume fraction to the ¼th power. The additional parameter e.g. α introduced in this scaling is related to the model drag parameters by employing an early-time latetime matching argument. Comparison with the scaled measurements of DeMauro et. al. suggest that the proposed modification is an effective formalism. Next, the connection between drag-based models and streamwise pressure difference-based expressions is explored by formulating simple analytical models that verify an empirical (Daniel and Wagner [2]) upstream-downstream expression. Though simple, these models provide physics-based approached describing shock particle curtain interaction behavior.

This paper presents a die-embedded glass interposer with minimum warpage for 5G/6G applications. The interposer performs high integration with low-loss interconnects by embedding multiple chips in the same glass substrate and interconnecting the chips through redistributive layers (RDL). Novel processes for cavity creation, multi-die embedding, carrier- less RDL build up and heat spreader attachment are proposed and demonstrated in this work. Performance of the interposer from 1 GHz to 110 GHz are evaluated. This work provides an advanced packaging solution for low-loss die-to-die and die-to-package interconnects, which is essential to high performance wireless system integration.

Prescriptive approaches for the cybersecurity of digital nuclear instrumentation and control (I&C) systems can be cumbersome and costly. These considerations are of particular concern for advanced reactors that implement digital technologies for monitoring, diagnostics, and control. A risk-informed performance-based approach is needed to enable the efficient design of secure digital I&C systems for nuclear power plants. This paper presents a tiered cybersecurity analysis (TCA) methodology as a graded approach for cybersecurity design. The TCA is a sequence of analyses that align with the plant, system, and component stages of design. Earlier application of the TCA in the design process provides greater opportunity for an efficient graded approach and defense-in-depth. The TCA consists of three tiers. Tier 1 is design and impact analysis. In Tier 1 it is assumed that the adversary has control over all digital systems, components, and networks in the plant, and that the adversary is only constrained by the physical limitations of the plant design. The plant's safety design features are examined to determine whether the consequences of an attack by this cyber-enabled adversary are eliminated or mitigated. Accident sequences that are not eliminated or mitigated by security by design features are examined in Tier 2 analysis. In Tier 2, adversary access pathways are identified for the unmitigated accident sequences, and passive measures are implemented to deny system and network access to those pathways wherever feasible. Any systems with remaining susceptible access pathways are then examined in Tier 3. In Tier 3, active defensive cybersecurity architecture features and cybersecurity plan controls are applied to deny the adversary the ability to conduct the tasks needed to cause a severe consequence. Tier 3 is not performed in this analysis because of the design maturity required for this tier of analysis.

Multiple Input Multiple Output (MIMO) vibration testing provides the capability to expose a system to a field environment in a laboratory setting, saving both time and money by mitigating the need to perform multiple and costly large-scale field tests. However, MIMO vibration test design is not straightforward oftentimes relying on engineering judgment and multiple test iterations to determine the proper selection of response Degree of Freedom (DOF) and input locations that yield a successful test. This work investigates two DOF selection techniques for MIMO vibration testing to assist with test design, an iterative algorithm introduced in previous work and an Optimal Experiment Design (OED) approach. The iterative-based approach downselects the control set by removing DOF that have the smallest impact on overall error given a target Cross Power Spectral Density matrix and laboratory Frequency Response Function (FRF) matrix. The Optimal Experiment Design (OED) approach is formulated with the laboratory FRF matrix as a convex optimization problem and solved with a gradient-based optimization algorithm that seeks a set of weighted measurement DOF that minimize a measure of model prediction uncertainty. The DOF selection approaches are used to design MIMO vibration tests using candidate finite element models and simulated target environments. The results are generalized and compared to exemplify the quality of the MIMO test using the selected DOF.

High-altitude electromagnetic pulse events are a growing concern for electric power grid vulnerability assessments and mitigation planning, and accurate modeling of surge arrester mitigations installed on the grid is necessary to predict pulse effects on existing equipment and to plan future mitigation. While some models of surge arresters at high frequency have been proposed, experimental backing for any given model has not been shown. This work examines a ZnO lightning surge arrester modeling approach previously developed for accurate prediction of nanosecond-scale pulse response. Four ZnO metal-oxide varistor pucks with different sizes and voltage ratings were tested for voltage and current response on a conducted electromagnetic pulse testbed. The measured clamping response was compared to SPICE circuit models to compare the electromagnetic pulse response and validate model accuracy. Results showed good agreement between simulation results and the experimental measurements, after accounting for stray testbed inductance between 100 and 250 nH.

Puerto Rico faced a double strike from hurricanes Irma and Maria in 2017. The resulting damage required a comprehensive rebuild of electric infrastructure. There are plans and pilot projects to rebuild with microgrids to increase resilience. This paper provides a techno-economic analysis technique and case study of a potential future community in Puerto Rico that combines probabilistic microgrid design analysis with tiered circuits in building energy modeling. Tiered circuits in buildings allow electric load reduction via remote disconnection of non-critiñl circuits during an emergency. When coupled to a microgrid, tiered circuitry can reduce the chances of a microgrid's storage and generation resources being depleted. The analysis technique is applied to show 1) Approximate cost savings due to a tiered circuit structure and 2) Approximate cost savings gained by simultaneously considering resilience and sustainability constraints in the microgrid optimization. The analysis technique uses a resistive capacitive thermal model with load profiles for four tiers (tier 1-3 and non-critical loads). Three analyses were conducted using: 1) open-source software called Tiered Energy in Buildings and 2) the Microgrid Design Toolkit. For a fossil fuel based microgrid 30% of the total microgrid costs of 1.18 million USD were calculated where the non-tiered case keeps all loads 99.9% available and the tiered case keeps tier 1 at 99.9%, tier 2 at 95%, tier 3 at 80% availability, with no requirement on non-critical loads. The same comparison for a sustainable microgrid showed 8% cost savings on a 5.10 million USD microgrid due to tiered circuits. The results also showed 6-7% cost savings when our analysis technique optimizes sustainability and resilience simultaneously in comparison to doing microgrid resilience analysis and renewables net present value analysis independently. Though highly specific to our case study, similar assessments using our analysis technique can elucidate value of tiered circuits and simultaneous consideration of sustainability and resilience in other locations.

Subhourly changes in solar irradiance can lead to energy models being biased high if realistic distributions of irradiance values are not reflected in the resource data and model. This is particularly true in solar facility designs with high inverter loading ratios (ILRs). When resource data with sufficient temporal and spatial resolution is not available for a site, synthetic variability can be added to the data that is available in an attempt to address this issue. In this work, we demonstrate the use of anonymized commercial resource datasets with synthetic variability and compare results with previous estimates of model bias due to inverter clipping and increasing ILR.

Experiments were conducted on a wave tank model of a bottom raised oscillating surge wave energy converter (OSWEC) model in regular waves. The OSWEC model shape was a thin rectangular flap, which was allowed to pitch in response to incident waves about a hinge located at the intersection of the flap and the top of the supporting foundation. Torsion springs were added to the hinge in order to position the pitch natural frequency at the center of the wave frequency range of the wave maker. The flap motion as well as the loads at the base of the foundation were measured. The OSWEC was modeled analytically using elliptic functions in order to obtain closed form expressions for added mass and radiation damping coefficients, along with the excitation force and torque. These formulations were derived and reported in a previous publication by the authors. While analytical predictions of the foundation loads agree very well with experiments, large discrepancies are seen in the pitch response close to resonance. These differences are analyzed by conducting a sensitivity study, in which system parameters, including damping and added mass values, are varied. The likely contributors to the differences between predictions and experiments are attributed to tank reflections, standing waves that can occur in long, narrow wave tanks, as well as the thin plate assumption employed in the analytical approach.