Expansion techniques are powerful tools that can take a limited measurement set and provide information on responses at unmeasured locations. Expansion techniques are used in dynamic environments specifications, full field stress measurements, model calibration, and other calculations that require response at locations not measured. However, the process of modal expansion techniques such as SEREP (System Equivalent Reduction Expansion Process) has error with the projection of the measurement set of degrees of freedom to the expanded degrees of freedom. Empirical evidence has been used in the past to qualitatively determine the error. In recent years, the modal projection error was developed to quantify the error through a projection between different domains. The modal projection error is used in this paper to demonstrate the use of the metric in quantifying the error of the expansion process and to quantify which modes of the expansion process are the most important.
The precise estimation of performance loss rate (PLR) of photovoltaic (PV) systems is vital for reducing investment risks and increasing the bankability of the technology. Until recently, the PLR of fielded PV systems was mainly estimated through the extraction of a linear trend from a time series of performance indicators. However, operating PV systems exhibit failures and performance losses that cause variability in the performance and may bias the PLR results obtained from linear trend techniques. Change-point (CP) methods were thus introduced to identify nonlinear trend changes and behaviour. The aim of this work is to perform a comparative analysis among different CP techniques for estimating the annual PLR of eleven grid-connected PV systems installed in Cyprus. Outdoor field measurements over an 8-year period (June 2006-June 2014) were used for the analysis. The obtained results when applying different CP algorithms to the performance ratio time series (aggregated into monthly blocks) demonstrated that the extracted trend may not always be linear but sometimes can exhibit nonlinearities. The application of different CP methods resulted to PLR values that differ by up to 0.85% per year (for the same number of CPs/segments).
For the resiliency of both small and large distribution systems, the concept of microgrids is arising. The ability for sections of the distribution system to be 'self-sufficient' and operate under their own energy generation is a desirable concept. This would allow for only small sections of the system to be without power after being affected by abnormal events such as a fault or a natural disaster, and allow for a greater number of consumers to go through their lives as normal. Research is needed to determine how different forms of generation will perform in a microgrid, as well as how to properly protect an islanded system. While synchronous generators are well understood and generally accepted amongst utility operators, inverter-based resources (IBRs) are less common. An IBR's fault characteristic varies between manufacturers and is heavily based on the internal control scheme. Additionally, with the internal protections of these devices to not damage the switching components, IBRs are usually limited to only 1.1-2.5p.u. of the rated current, depending on the technology. This results in traditional protection methods such as overcurrent devices being unable to 'trip' in a microgrid with high IBR penetration. Moreover, grid-following inverters (commonly used for photovoltaic systems) require a voltage source to synchronize with before operating. Also, these inverters do not provide any inertia to a system. On the other hand, grid-forming inverters can operate as a primary voltage source, and provide an 'emulated inertia' to the system. This study will look at a small islanded system with a grid-forming inverter, and a grid-following inverter subjected to a line-to-ground fault.
A crucial component of field testing is the utilization of numerical models to better understand the system and the experimental data being collected. Meshing and modeling field tests is a complex and computationally demanding problem. Hexahedral elements cannot always reproduce experimental dimensions leading to grid orientation or geometric errors. Voronoi meshes can match complex geometries without sacrificing orthogonality. As a result, here we present a high-resolution 3D numerical study for the BATS heater test at the WIPP that compares both a standard non-deformed cartesian mesh along with a Voronoi mesh to match field data collected during a salt heater experiment.
Neural networks (NN)s have been increasingly proposed as surrogates for approximation of systems with computationally expensive physics for rapid online evaluation or exploration. As these surrogate models are integrated into larger optimization problems used for decision making, there is a need to verify their behavior to ensure adequate performance over the desired parameter space. We extend the ideas of optimization-based neural network verification to provide guarantees of surrogate performance over the feasible optimization space. In doing so, we present formulations to represent neural networks within decision-making problems, and we develop verification approaches that use model constraints to provide increasingly tight error estimates. We demonstrate the capabilities on a simple steady-state reactor design problem.
Femtosecond laser electronic excitation tagging (FLEET) is a powerful unseeded velocimetry technique typically used to measure one component of velocity along a line, or two or three components from a dot. In this Letter, we demonstrate a dotted-line FLEET technique which combines the dense profile capability of a line with the ability to perform two-component velocimetry with a single camera on a dot. Our set-up uses a single beam path to create multiple simultaneous spots, more than previously achieved in other FLEET spot configurations. We perform dotted-line FLEET measurements downstream of a highly turbulent, supersonic nitrogen free jet. Dotted-line FLEET is created by focusing light transmitted by a periodic mask with rectangular slits of 1.6 × 40 mm2 and an edge-to-edge spacing of 0.5 mm, then focusing the imaged light at the measurement region. Up to seven symmetric dots spaced approximately 0.9 mm apart, with mean full-width at half maximum diameters between 150 and 350 µm, are simultaneously imaged. Both streamwise and radial velocities are computed and presented in this Letter.
This chapter deals with experimental dynamic substructures which are reduced order models that can be coupled with each other or with finite element derived substructures to estimate the system response of the coupled substructures. A unifying theoretical framework in the physical, modal or frequency domain is reviewed with examples. The major issues that have hindered experimental based substructures are addressed. An example is demonstrated with the transmission simulator method that overcomes the major historical difficulties. Guidelines for the transmission simulator design are presented.
Software sustainability is critical for Computational Science and Engineering (CSE) software. Measuring sustainability is challenging because sustainability consists of many attributes. One factor that impacts software sustainability is the complexity of the source code. This paper introduces an approach for utilizing complexity data, with a focus on hotspots of and changes in complexity, to assist developers in performing code reviews and inform project teams about longer-term changes in sustainability and maintainability from the perspective of cyclomatic complexity. We present an analysis of data associated with four real-world pull requests to demonstrate how the metrics may help guide and inform the code review process and how the data can be used to measure changes in complexity over time.
A 0.2-2 GHz digitally programmable RF delay element based on a time-interleaved multi-stage switched-capacitor (TIMS-SC) approach is presented. The proposed approach enables hundreds of ns of broadband RF delay by employing sample time expansion in multiple stages of switched-capacitor storage elements. The delay element was implemented in a 45 nm SOI CMOS process and achieves a 2.55-448.6 ns programmable delay range with < 0.12% delay variation across 1.8 GHz of bandwidth at maximum delay, 2.42 ns programmable delay steps, and 330 ns/mm2 area efficiency. The device achieves 24 dB gain, 7.1 dB noise figure, and consumes 80 mW from a 1 V supply with an active area of 1.36 mm2.
We have extended the computational singular perturbation (CSP) method to differential algebraic equation (DAE) systems and demonstrated its application in a heterogeneous-catalysis problem. The extended method obtains the CSP basis vectors for DAEs from a reduced Jacobian matrix that takes the algebraic constraints into account. We use a canonical problem in heterogeneous catalysis, the transient continuous stirred tank reactor (T-CSTR), for illustration. The T-CSTR problem is modelled fundamentally as an ordinary differential equation (ODE) system, but it can be transformed to a DAE system if one approximates typically fast surface processes using algebraic constraints for the surface species. We demonstrate the application of CSP analysis for both ODE and DAE constructions of a T-CSTR problem, illustrating the dynamical response of the system in each case. We also highlight the utility of the analysis in commenting on the quality of any particular DAE approximation built using the quasi-steady state approximation (QSSA), relative to the ODE reference case.
Ship emissions can form linear cloud structures, or ship tracks, when atmospheric water vapor condenses on aerosols in the ship exhaust. These structures are of interest because they are observable and traceable examples of MCB, a mechanism that has been studied as a potential approach for solar climate intervention. Ship tracks can be observed throughout the diurnal cycle via space-borne assets like the advanced baseline imagers on the national oceanic and atmospheric administration geostationary operational environmental satellites, the GOES-R series. Due to complex atmospheric dynamics, it can be difficult to track these aerosol perturbations over space and time to precisely characterize how long a single emission source can significantly contribute to indirect radiative forcing. We propose an optical flow approach to estimate the trajectories of ship-emitted aerosols after they begin mixing with low boundary layer clouds using GOES-17 satellite imagery. Most optical flow estimation methods have only been used to estimate large scale atmospheric motion. We demonstrate the ability of our approach to precisely isolate the movement of ship tracks in low-lying clouds from the movement of large swaths of high clouds that often dominate the scene. This efficient approach shows that ship tracks persist as visible, linear features beyond 9 h and sometimes longer than 24 h.
We present optical metrology at the Sandia fog chamber facility. Repeatable and well characterized fogs are generated under different atmospheric conditions and applied for light transport model validation and computational sensing development.
Pre-chamber ignition has demonstrated capability to increase internal combustion engine in-cylinder burn rates and enable the use of low engine-out pollutant emission combustion strategies. In the present study, newly designed passive pre-chambers with different nozzle-hole patterns - that featured combinations of radial and axial nozzles - were experimentally investigated in an optically accessible, single-cylinder research engine. The pre-chambers analyzed had a narrow throat geometry to increase the velocity of the ejected jets. In addition to a conventional inductive spark igniter, a nanosecond spark ignition system that promotes faster early burn rates was also investigated. Time-resolved visualization of ignition and combustion processes was accomplished through high-speed hydroxyl radical (OH*) chemiluminescence imaging. Pressure was measured during the engine cycle in both the main chamber and pre-chamber to monitor respective combustion progress. Experimental heat release rates (HRR) calculated from the measured pressure profiles were used as inputs for two different GT-Power 1D simulations to evaluate the pre-chamber jet-exit momentum and penetration distance. The first simulation used both the calculated main-chamber and pre-chamber HRR, while the second used only the main chamber HRR with the pre-chamber HRR modeled. Results show discrepancies between the models mainly in the pressurization of the pre-chamber which in turn affected jet penetration rate and highlights the sensitivity of the simulation results to proper input selection. Experimental results further show increased pressurization, with an associated acceleration of jet penetration, when operating with nanosecond spark ignition systems regardless of the pre-chamber tip geometry used.
In order to evaluate the time evolution of avalanche breakdown in wide and ultra-wide bandgap devices, we have developed a cable pulser experimental setup that can evaluate the time-evolution of the terminating impedance for a semiconductor device with a time resolution of 130 ps. We have utilized this pulser setup to evaluate the time-to-breakdown of vertical Gallium Nitride and Silicon Carbide diodes for possible use as protection elements in the electrical grid against fast transient voltage pulses (such as those induced by an electromagnetic pulse event). We have found that the Gallium Nitride device demonstrated faster dynamics compared to the Silicon Carbide device, achieving 90% conduction within 1.37 ns compared to the SiC device response time of 2.98 ns. While the Gallium Nitride device did not demonstrate significant dependence of breakdown time with applied voltage, the Silicon Carbide device breakdown time was strongly dependent on applied voltage, ranging from a value of 2.97 ns at 1.33 kV to 0.78 ns at 2.6 kV. The fast response time (< 5 ns) of both the Gallium Nitride and Silicon Carbide devices indicate that both materials systems could meet the stringent response time requirements and may be appropriate for implementation as protection elements against electromagnetic pulse transients.
To keep pace with the demand for innovation through scientific computing, modern scientific software development is increasingly reliant upon a rich and diverse ecosystem of software libraries and toolchains. Research software engineers (RSEs) responsible for that infrastructure perform highly integrative work, acting as a bridge between the hardware, the needs of researchers, and the software layers situated between them; relatively little, however, has been written about the role played by RSEs in that work and what support they need to thrive. To that end, we present a two-part report on the development of half-precision floating point support in the Kokkos Ecosystem. Half-precision computation is a promising strategy for increasing performance in numerical computing and is particularly attractive for emerging application areas (e.g., machine learning), but developing practicable, portable, and user-friendly abstractions is a nontrivial task. In the first half of the paper, we conduct an engineering study on the technical implementation of the Kokkos half-precision scalar feature and showcase experimental results; in the second half, we offer an experience report on the challenges and lessons learned during feature development by the first author. We hope our study provides a holistic view on scientific library development and surfaces opportunities for future studies into effective strategies for RSEs engaged in such work.
Demonstration of broadband nanosecond output from a burst-mode-pumped noncolinear optical parametric oscillator (NOPO) has been achieved at 40 kHz. The NOPO is pumped by 355-nm output at 50 mJ/pulse for 45 pulses. A bandwidth of 540 cm-1 was achieved from the OPO with a conversion efficiency of 10% for 5 mJ/pulse. Higher bandwidths up to 750 cm-1 were readily achievable at reduced performance and beam quality. The broadband NOPO output was used for a planar BOXCARS phase matching scheme for N2 CARS measurements in a near adiabatic H2/air flame. Single-shot CARS measurements were taken for equivalence ratios of φ=0.52-0.86 for temperatures up to 2200 K.
Large scale non-intrusive inspection (NII) of commercial vehicles is being adopted in the U.S. at a pace and scale that will result in a commensurate growth in adjudication burdens at land ports of entry. The use of computer vision and machine learning models to augment human operator capabilities is critical in this sector to ensure the flow of commerce and to maintain efficient and reliable security operations. The development of models for this scale and speed requires novel approaches to object detection and novel adjudication pipelines. Here we propose a notional combination of existing object detection tools using a novel ensembling framework to demonstrate the potential for hierarchical and recursive operations. Further, we explore the combination of object detection with image similarity as an adjacent capability to provide post-hoc oversight to the detection framework. The experiments described herein, while notional and intended for illustrative purposes, demonstrate that the judicious combination of diverse algorithms can result in a resilient workflow for the NII environment.
This paper presents a type-IV wind turbine generator (WTG) model developed in MATLAB/Simulink. An aerodynamic model is used to improve an electromagnetic transient model. This model is further developed by incorporating a single-mass model of the turbine and including generator torque control from an aerodynamic model. The model is validated using field data collected from an actual WTG located in the Scaled Wind Farm Technology (SWiFT) facility. The model takes the nacelle wind speed as an estimate. To ensure the model and the SWiFT WTG field data is compared accurately, the wind speed is estimated using a Kalman filter. Simulation results shows that using a single-mass model instead of a two-mass model for aerodynamic torque, including the generator torque control from SWiFT, estimating wind speed via the Kalman filter and tunning the synchronous generator, accurately represent the generator torque, speed, and power, compared to the SWiFT WTG field data.
We present a procedure for randomly generating realistic steady-state contingency scenarios based on the historical outage data from a particular event. First, we divide generation into classes and fit a probability distribution of outage magnitude for each class. Second, we provide a method for randomly synthesizing generator resilience levels in a way that preserves the data-driven probability distributions of outage magnitude. Finally, we devise a simple method of scaling the storm effects based on a single global parameter. We apply our methods using data from historical Winter Storm Uri to simulate contingency events for the ACTIVSg2000 synthetic grid on the footprint of Texas.
Integrating recent advancements in resilient algorithms and techniques into existing codes is a singular challenge in fault tolerance - in part due to the underlying complexity of implementing resilience in the first place, but also due to the difficulty introduced when integrating the functionality of a standalone new strategy with the preexisting resilience layers of an application. We propose that the answer is not to build integrated solutions for users, but runtimes designed to integrate into a larger comprehensive resilience system and thereby enable the necessary jump to multi-layered recovery. Our work designs, implements, and verifies one such comprehensive system of runtimes. Utilizing Fenix, a process resilience tool with integration into preexisting resilience systems as a design priority, we update Kokkos Resilience and the use pattern of VeloC to support application-level integration of resilience runtimes. Our work shows that designing integrable systems rather than integrated systems allows for user-designed optimization and upgrading of resilience techniques while maintaining the simplicity and performance of all-in-one resilience solutions. More application-specific choice in resilience strategies allows for better long-term flexibility, performance, and - importantly - simplicity.
This paper provides a study of the potential impacts of climate change on intermittent renewable energy resources, battery storage, and resource adequacy in Public Service Company of New Mexico's Integrated Resource Plan for 2020 - 2040. Climate change models and available data were first evaluated to determine uncertainty and potential changes in solar irradiance, temperature, and wind speed in NM in the coming decades. These changes were then implemented in solar and wind energy models to determine impacts on renewable energy resources in NM. Results for the extreme climate-change scenario show that the projected wind power may decrease by ~13% due to projected decreases in wind speed. Projected solar power may decrease by ~4% due to decreases in irradiance and increases in temperature in NM. Uncertainty in these climateinduced changes in wind and solar resources was accommodated in probabilistic models assuming uniform distributions in the annual reductions in solar and wind resources. Uncertainty in battery storage performance was also evaluated based on increased temperature, capacity fade, and degradation in roundtrip efficiency. The hourly energy balance was determined throughout the year given uncertainties in the renewable energy resources and energy storage. The loss of load expectation (LOLE) was evaluated for the 2040 No New Combustion portfolio and found to increase from 0 days/year to a median value of ~2 days/year due to potential reductions in renewable energy resources and battery storage performance and capacity. A rank-regression analyses revealed that battery round-trip efficiency was the most significant parameter that impacted LOLE, followed by solar resource, wind resource, and battery fade. An increase in battery storage capacity to ~30,000 MWh from a baseline value of ~14,000 MWh was required to reduce the median value of LOLE to ~0.2 days/year with consideration of potential climate impacts and battery degradation.
We present a field-deployable microfluidic immunoassay device in response to the need for sensitive, quantitative, and high-throughput protein detection at point-of-need. The portable microfluidic system facilitates eight magnetic bead-based sandwich immunoassays from raw samples in 45 minutes. An innovative bead actuation strategy was incorporated into the system to automate multiple sample process steps with minimal user intervention. The device is capable of quantitative and sensitive protein analysis with a 10 pg/ml detection limit from interleukin 6-spiked human serum samples. We envision the reported device offering ultrasensitive point-of-care immunoassay tests for timely and accurate clinical diagnosis.