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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Assessment of rare earth element fractionation in NIF implosions with radiochemically doped capsules

An ongoing experimental campaign at the National Ignition Facility (NIF) aims to measure neutron induced nuclear reaction cross–sections using radiochemically doped target capsules. Critical to this campaign is the ability to collect a representative sample of the reaction products using Solid Radiochemical Collectors (SRCs) fielded around the NIF chamber. The shot presented in this paper used a doped target capsule with a neopentane gas fill was to investigate the ratio of isotopes collected at three chamber angles. It was found that SRC samples of rare earth elements collected from NIF are representative of the ingoing dopant mix, thereby concluding that fractionation does not occur during a NIF implosion. This validates the doped capsule method for use in measuring neutron induced reaction cross-sections.

Capsule Doping↗
DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Using Energy Storage-Based Grid Forming Inverters for Operational Reserve in Hybrid Diesel Microgrids

In remote arctic communities, where access to a bulk electrical grid interconnection is not available, the implementation of islanded microgrids has been the most viable way to produce and distribute electricity services to their inhabitants. Historically, these islanded grids have relied primarily on diesel generators or hydropower resources to supply the baseload. However, this practice can result in increased expense due to the high costs associated with fuel transportation and the significant amounts of on-site storage necessary when fuel transportation is unavailable during winter months. In order to mitigate this problem, arctic microgrids have started to transition to a hybrid-source operational mode by incorporating renewable energy sources that are inherently variable in nature, such as wind or solar. Due to their highly stochastic behavior, these hybrid-source islanded microgrids can pose potential issues related to power quality due to introduction of rapid net load fluctuations and inability of diesel generators to respond rapidly. In addition, non-firm stochastic sources can require significant idling diesel generator resources to serve as spinning reserves, which is inefficient and wasteful. This work studies the problems that may arise in the transient dynamics of a real-world hybrid diesel microgrid when subjected to a loss of wind generation. Moreover, this work proposes a transition from a diesel spinning reserve to a battery energy-storage system (BESS) operating reserve scheme. The study of the proposed transition is important in establishing the fundamental implication of transient dynamics and the potential benefits of integrating a BESS as a spinning reserve in terms of stability, frequency nadir, and transient voltage deviation. The methods to investigate and validate the transient dynamics relied on both electromagnetic simulation models of GFMIs and a commercially available GFMI in an experimental power hardware-in-the-loop setup. The simulation results showed that the proposed operating reserve scheme improves the power quality of the system in terms of voltage deviation and frequency nadir when the microgrid is subjected to a loss of wind generation scenario. Depending on the simulation cases, adding a GFMI reduced the frequency nadir between 65.3% and 86.7%. Moreover, the reductions in the voltage deviations improved between 3.6% and 23.0%. From these results it can be concluded that the integration of a GFMI can reduce the frequency nadir in a hybrid diesel microgrid, and in turn, reduce diesel consumption, which improves system reliability while reducing fuel expenses. Furthermore, the novelty of this work relies on the fact that the offline simulation results were validated using a power hardware-in-the-loop platform that incorporated a 100 kVA commercially available GFMI as the device under test.

Hernandez-Alvidrez, Javier↗
DOE OSTI2022

Transverse Vector Decomposition Method for Analytical Inversion of Exoplanet Transit Spectra

Abstract We develop a new method for analytical inversion of binned exoplanet transit spectra and for retrieval of planet parameters. The method has a geometrical interpretation and treats each observed spectrum as a single vector r → in the multidimensional spectral space of observed bin values. We decompose the observed r → into two orthogonal components: a wavelength-independent component r → ∥ corresponding to the spectral mean across all observed bins, and a transverse component r → ⊥ that is wavelength dependent and contains the relevant information about the atmospheric chemistry. The method allows us to extract, without any prior assumptions or additional information, the relative mass (or volume) mixing ratios of the absorbers in the atmosphere, the scale height to stellar radius ratio, H / R S , and the atmospheric temperature. The method is illustrated and validated with several examples of increasing complexity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Route-Optimized Energy Management of Connected and Automated Multi-Mode Plug-In Hybrid Electric Vehicle Using Dynamic Programming

This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) that reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The PHEV used in this investigation is the second-generation Chevrolet Volt and as many as four instrumented vehicles were utilized simultaneously on road to acquire validation data. The optimization method used is dynamic programming (DP) paired with a reduced-order powertrain model to enable onboard embedded controller compatibility and computational efficiency in optimally blending CD, CS modes over the entire drive route. The objective of the optimizer is to enable future Connected and Automated Vehicles (CAVs) to best utilize onboard energy for minimum overall energy consumption based on speed and elevation profile information from Intelligent Transportation Systems (ITS), Internet of Things (IoT), High-definition Mapping, and onboard sensing technologies. Emphasis is placed on runtime minimization to quickly react and plan an optimal mode scheme in highly dynamic road conditions with minimal computational resources. On-road performance of the optimizer paired with automated CD and CS mode selection is evaluated on a fleet of four instrumented Chevrolet Volts in a variety of driving scenarios. Here, the results indicate variable energy savings depending on the drive route and initial battery SOC with potential ranging between 2 to 12% and less than 7 seconds initial optimization for a 24-mile drive cycle.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Detection and variability of combustion-derived vapor in an urban basin

Abstract. Water emitted during combustion may comprise a significant portion of ambient humidity (> 10 %) in urban areas, where combustion emissions are strongly focused in space and time. Stable water vapor isotopes can be used to apportion measured humidity values between atmospherically transported and combustion-derived water vapor, as combustion-derived vapor possesses an unusually negative deuterium excess value (d-excess, d = δ 2 H − 8 δ 18 O). We investigated the relationship between the d-excess of atmospheric vapor, ambient CO 2 concentrations, and atmospheric stability across four winters in Salt Lake City, Utah. We found a robust inverse relationship between CO 2 excess above background and d-excess on sub-diurnal to seasonal timescales, which was most prominent during periods of strong atmospheric stability that occur during Salt Lake City winter. Using a Keeling-style mixing model approach, and assuming a molar ratio of H 2 O to CO 2 in emissions of 1.5, we estimated the d-excess of combustion-derived vapor in Salt Lake City to be −179 ± 17 ‰, consistent with the upper limit of theoretical estimates. Based on this estimate, we calculate that vapor from fossil fuel combustion often represents 5–10 % of total urban humidity, with a maximum estimate of 16.7 %, consistent with prior estimates for Salt Lake City. Moreover, our analysis highlights that changes in the observed d-excess during periods of high atmospheric stability cannot be explained without a vapor source possessing a strongly negative d-excess value. Further refinements in this humidity apportionment method, most notably empirical validation of the d-excess of combustion vapor or improvements in the estimation of the background d-excess value in the absence of combustion, can yield more certain estimates of the impacts of fossil fuel combustion on urban humidity and meteorology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Sediment Resuspension and Transport in Water Distribution Storage Tanks

Computational and experimental studies were conducted to better understand conditions that affect particle resuspension and movement in water storage tanks. Parameters that were investigated included inlet/outlet (I/O) line location and diameter, flow rate, particle size, and filling versus draining cycles. Simulation results showed that smaller particle sizes, higher flow rates, and draining cycles yielded the greatest potential for particle resuspension, which was generally limited to regions near the I/O line. Small‐scale experiments were also performed using different sizes of glass beads and silica sand; the results generally validated the models. Mitigation methods were also presented to reduce the amount of particle resuspension. A pipe that extended from the I/O line into the tank (slightly above the bottom floor) was found to significantly reduce the potential for particle resuspension in both the computational models and experiments.

Ho, Clifford K.↗
DOE OSTI2012

The Ongoing Impact of the U.S. Fast Reactor Integral Experiments Program

The creation of a large database of integral fast reactor physics experiments advanced nuclear science and technology in ways that were unachievable by less capital intensive and operationally challenging approaches. They enabled the compilation of integral physics benchmark data, validated (or not) analytical methods, and provided assurance of future rector designs The integral experiments performed at Argonne National Laboratory (ANL) represent decades of research performed to support fast reactor design and our understanding of neutronics behavior and reactor physics measurements. Experiments began in 1955 with the Zero Power Reactor No. 3 (ZPR-3) and terminated with the Zero Power Physics Reactor (ZPPR, originally the Zero Power Plutonium Reactor) in 1990 at the former ANL-West site in Idaho, which is now part of the Idaho National Laboratory (INL). Two additional critical assemblies, ZPR-6 and ZPR-9, operated at the ANL-East site in Illinois. A total of 128 fast reactor assemblies were constructed with these facilities [1]. The infrastructure and measurement capabilities are too expensive to be replicated in the modern era, making the integral database invaluable as the world pushes ahead with development of liquid metal cooled reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Cleaner Energy for Cars

Representing the Center for Catalytic Hydrocarbon Functionalization (CCHF), this document is one of the entries in the Ten Hundred and One Word Challenge. As part of the challenge, the 46 Energy Frontier Research Centers were invited to represent their science in images, cartoons, photos, words and original paintings, but any descriptions or words could only use the 1000 most commonly used words in the English language, with the addition of one word important to each of the EFRCs and the mission of DOE: energy. The mission of CCHF is to develop, validate, and optimize new methods to rearrange the bonds of hydrocarbons, implement enzymatic strategies into synthetic systems, and design optimal environments for catalysts that can be used to reversibly functionalize hydrocarbons, especially for more efficient use of natural gas including low temperature conversion to liquid fuels.

08 HYDROGEN↗
DOE OSTI2015

Upper Subcritical Limit Calculations with Correlated Integral Experiments

The American National Standards Institute (ANSI) and American Nuclear Society (ANS) standard for Validation of Neutron Transport Methods for Nuclear Criticality Safety Calculations defines the Upper Subcritical Limit (USL) as “a limit on the calculated k effective value established to ensure that conditions calculated to be subcritical will actually be subcritical.” Often, USL calculations are based on statistical techniques that infer information about a nuclear system of interest (application) from a set of known/well characterized similar systems (experiments). In determining a USL, it is common to statistically determine a calculation bias and bias uncertainty. Bias is “the systematic difference between calculated results and experimental data.” The bias uncertainty is “the uncertainty that accounts for the combined effects of uncertainties in the benchmarks, the calculational models of the benchmarks, and the calculational methods.” Both the bias and the bias uncertainty are often inferred through statistical methods applied to the selected set of experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Upper Subcritical Calculations Based on Correlated Data

The American National Standards Institute and American Nuclear Society standard for Validation of Neutron Transport Methods for Nuclear Criticality Safety Calculations defines the upper subcritical limit (USL) as “a limit on the calculated k-effective value established to ensure that conditions calculated to be subcritical will actually be subcritical.” Often, USL calculations are based on statistical techniques that infer information about a nuclear system of interest from a set of known/well-characterized similar systems. The work in this paper is part of an active area of research to investigate the way traditional trending analysis is used in the nuclear industry, and in particular, the research is assessing the impact of the underlying assumption that the experimental data being analyzed for USL calculations are statistically independent. In contrast, the multiple experiments typically used for USL calculations can be correlated because they are often performed at the same facilities using the same materials and measurement techniques. This paper addresses this issue by providing a set of statistical inference methods to calculate the bias and bias uncertainty based on the underlying assumption that the experimental data are correlated. Methods to quantify these correlations are the subject of a companion paper and will not be discussed here. The newly proposed USL methodology is based on the assumption that the integral experiments selected for use in the establishment of the USL are sufficiently applicable and that experimental correlations are known. Under the assumption of uncorrelated data, the new methods collapse directly to familiar USL equations currently used. We will demonstrate our proposed methods on real data and compare them to calculations of currently used methods such as USLSTATS and NUREG/CR-6698. Lastly, we will also demonstrate the effect experiment correlations can have on USL calculations.

42 ENGINEERING↗
DOE OSTI2017

Test Methodologies for Hydrogen Sensor Performance Assessment: Chamber vs. Flow Through Test Apparatus: Preprint

Certification of hydrogen sensors to standards often prescribes using large-volume test chambers [1, 2]. However, feedback from stakeholders such as sensor manufacturers and end-users indicate that chamber test methods are often viewed as too slow and expensive for routine assessment. Flow through test methods potentially are an efficient, cost-effective alternative for sensor performance assessment. A large number of sensors can be simultaneously tested, in series or in parallel, with an appropriate flow through test fixture. The recent development of sensors with response times of less than 1s mandates improvements in equipment and methodology to properly capture the performance of this new generation of fast sensors; flow methods are a viable approach for accurate response and recovery time determinations, but there are potential drawbacks. According to ISO 26142 [1], flow through test methods may not properly simulate ambient applications. In chamber test methods, gas transport to the sensor can be dominated by diffusion which is viewed by some users as mimicking deployment in rooms and other confined spaces. Alternatively, in flow through methods, forced flow transports the gas to the sensing element. The advective flow dynamics may induce changes in the sensor behaviour relative to the quasi-quiescent condition that may prevail in chamber test methods. One goal of the current activity in the JRC and NREL sensor laboratories [3, 4] is to develop a validated flow through apparatus and methods for hydrogen sensor performance testing. In addition to minimizing the impact on sensor behaviour induced by differences in flow dynamics, challenges associated with flow through methods include the ability to control environmental parameters (humidity, pressure and temperature) during the test and changes in the test gas composition induced by chemical reactions with upstream sensors. Guidelines on flow through test apparatus design and protocols for the evaluation of hydrogen sensor performance are being developed. Various commercial sensor platforms (e.g., thermal conductivity, catalytic and metal semiconductor) were used to demonstrate the advantages and issues with the flow through methodology.

14 SOLAR ENERGY↗
DOE OSTI2015

Computational redesign reveals allosteric mutation hotspots of organophosphate hydrolase that enhance organophosphate hydrolysis

Organophosphates are widely used for peaceful (agriculture) and military purposes (chemical warfare agents). The extraordinary toxicity of organophosphates and the risk of deployment, make it critical to develop means for their rapid and efficient deactivation. Organophosphate hydrolase (OPH) already plays an important role in organophosphate remediation, but is insufficient for therapeutic or prophylactic purposes primarily due to low substrate affinity. Current efforts focus on directly modifying the active site to differentiate substrate specificity and increase catalytic activity. Here, we present a novel strategy for enhancing the general catalytic efficiency of OPH through computational redesign of the residues that are allosterically coupled to the active site and validated our design by mutagenesis. Specifically, we identify five such hot-spot residues for allosteric regulation and assay these mutants for hydrolysis activity against paraoxon, a chemical-weapons simulant. A high percentage of the predicted mutants exhibit enhanced activity over wild-type (k cat =16.63 s -1 ), such as T199I/T54I (899.5 s -1 ) and C227V/T199I/T54I (848 s -1 ), while the Km remains relatively unchanged in our high-throughput cell-free expression system. Further computational studies of protein dynamics reveal four distinct distal regions coupled to the active site that display significant changes in conformation dynamics upon these identified mutations. These results validate a computational design method that is both efficient and easily adapted as a general procedure for enzymatic enhancement.

organophosphate hydrolase↗
DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Scheduling and Control of Flexible Building Loads for Grid Services Based on a Virtual Battery Model

This paper presents a framework for modeling, scheduling, and controlling residential thermostatically controlled loads (TCLs) to provide multiple grid services, such as energy shifting, peak load reduction, and ancillary services. A modeling method is proposed to characterize the aggregate flexibility from heterogeneous TCLs using a battery-equivalent model. Based on the flexibility model, a multi-period optimal scheduling formulation is developed to best utilize the flexibility from building loads and maximize total benefits from stacked value streams. An algorithm is proposed to control individual TCLs to follow the desired power consumption in real-time. The proposed methods are illustrated and validated through simulations.

Wu, Di↗
DOE OSTI2021

Detection, monitoring, and determination of location of changes in metallic structures using multimode acoustic signals

Acoustic transducers generate and receive acoustic signals at multiple locations along a surface of rigid structure, wherein longitudinal spacing between transducer locations define measurement zones. Acoustic signals with chosen amplitude-time-frequency characteristics excite multiple vibration modes in the structure within each zone. Small mechanical changes in inspection zones lead to scattering and attenuation of broadband acoustic signals, which are detectable as changes in received signal characteristics as part of a through-transmission technique. Additional use of short, narrowband pulse acoustic signals as part of a pulse-echo technique allows determination of the relative location of the mechanical change within each zone based on the differential delay profiles. For accurate acoustic modeling and simulation, the mesh size, time step, time delay, and time-window size are optimized. Frequency normalization of the Short-Time Fourier Transform of acoustic response output improves experiment-simulation cross-validation. Applications of the method to structures with arbitrarily complex geometries are also demonstrated.

Findikoglu, Alp Tugrul↗