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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Rapid denitrification of nitrate-contaminated groundwater in a low-gradient blackwater stream valley

Leaching of excess nitrogen (N) to groundwater in fertilized landscapes can overwhelm natural biogeochemical processes and cause long-term eutrophication of aquatic systems. We investigated N fate and transport from an intensively managed short-rotation woody crop (Pinus taeda) plantation through the riparian zone of an intermittent, low-gradient blackwater stream. Fertilization of the P. taeda plantation on the uplands resulted in contamination of groundwater with nitrate concentrations between 0.9 and 1.9 mg N L -1 . No corresponding increase in nitrate was observed in stream water or shallow groundwater in the riparian zone. Groundwater travel-time modeling predicted that N from near-stream, upland plantation areas should have reached streams during the monitoring period. Two years of measuring N species in well water in contrasting landscape positions (within the plantation, swale, riparian edge, forested hillslope, and valley), indicated rapid nitrate transformation and denitrification within the forested wetland valleys. Denitrification in the shallow groundwater system within the toeslopes and the riparian zone was estimated to have removed > 90% of nitrate. Finally, these results highlight the importance of riparian zones as pathways for the removal of N and for controlling downstream N loads.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Imputation of urban environmental sensor data using gated attention bidirectional long short-term memory (GA-BiLSTM): methods, performance, and implications

Urban environmental monitoring networks frequently encounter significant data gaps due to sensor malfunctions, environmental disturbances, and communication failures. Reliable approaches to address these gaps are essential for ensuring the continuity and quality of environmental data streams. In this study, we developed a gated attention bidirectional long short-term memory (GA-BiLSTM) model to impute missing data in a dense urban monitoring network. Using observations from the CROCUS network in Chicago, we evaluated GA-BiLSTM against widely used approaches (XGBoost and K-nearest neighbors) under scenarios of both short-term intermittent gaps and prolonged outages. GA-BiLSTM consistently outperformed comparative methods, particularly during extended outages of up to ten days, demonstrating its ability to capture spatiotemporal dependencies across sensor nodes. Beyond performance metrics, feature importance and spatial network analyses highlighted the unexpected but critical predictive role of peripheral rural nodes, underlining their strategic value for maintaining robust urban monitoring systems. These results emphasize that advanced imputation methods can substantially improve the reliability of environmental monitoring networks and support more resilient data infrastructures for urban sustainability.

Data imputation↗
DOE OSTI2020

Electrochemical Reduction Selectivity of Crotonaldehyde on Copper

Lignocellulosic waste is a potential feedstock for the generation of fuels and commodity chemicals, but existing conversion methods are too cost-intensive to be viable long-term solutions. Electrochemical reductions are promising for decentralized biomass valorization due to their modular scaling and capacity to run intermittently and without high temperatures or pressures. Using crotonaldehyde as a multi-functional model compound for the many partially unsaturated oxygenates found in processed biomass, we here demonstrate the production of butanal, butanol, butene, and butane (variously useful as commodity chemicals and major components of liquified petroleum gas) under ambient conditions by reductive bulk electrolysis with a copper mesh working electrode. We identify an optimum potential for reduced organic production under the reaction conditions and compare product distributions from reductions of intermediate species to further propose branching reaction pathways. Though butanal is typically the most abundant product from crotonaldehyde reduction, most of the butene and butane appear to result from a pathway involving initial reduction of the aldehyde group. We discuss evidence that selectivity is driven by interplay between crotonaldehyde reduction, local pH shifts due to the hydrogen evolution reaction, and changes in site reactivity and availability due to electrode fouling. This demonstration of model electrochemical biomass valorization also serves to inform further exploration into reduction of multi-functional molecules and electrochemical biomass processing in general.

biomass↗
DOE OSTI2021

Insights on the continuous representations of piecewise-smooth nonlinear systems: limits of applicability and effectiveness

Dynamical systems subject to intermittent contact are often modeled with piecewise-smooth contact forces. However, the discontinuous nature of the contact can cause inaccuracies in numerical results or failure in numerical solvers. Representing the piecewise contact force with a continuous and smooth function can mitigate these problems, but not all continuous representations may be appropriate for this use. Here, five representations used by previous researchers (polynomial, rational polynomial, hyperbolic tangent, arctangent, and logarithm-arctangent functions) are studied to determine which ones most accurately capture nonlinear behaviors including super- and subharmonic resonances, multiple solutions, and chaos. The test case is a single-DOF forced Duffing oscillator with freeplay nonlinearity, solved using direct time integration. This work intends to expand on past studies by determining the limits of applicability for each representation and what numerical problems may occur.

42 ENGINEERING↗
DOE OSTI2024

The environmental impact of hydropower: a systematic review of the ecological effects of sub-daily flow variability on riverine fish

Hydropower can help facilitate power grid decarbonization because it can respond to short-term changes in power demand and is comparatively more reliable than intermittent wind and solar. However, flexible hydropower operations can create rapid and abnormal fluctuations in downstream flow conditions, which can negatively impact aquatic ecosystems. Accordingly, we conducted a systematic review on the ecological effects of hydropower-driven sub-daily flow variability (SDFV) on riverine fishes. We reviewed and synthesized 109 articles relevant to fish-SDFV relationships from seven sources, most of which focused on Salmonids in North America and northern and western Europe and were published in the last 15 years. We found strong agreement in the literature that SDFV increases fish stranding risk, destabilizes habitat, and decreases production and diversity. We found moderate agreement that SDFV interrupts fish reproduction, increases or has no impact on condition, and prompts or discourages movement depending on local channel conditions. We found little to no agreement for relationships between SDFV and mortality, physiology, and behavior. The effects of SDFV on riverine fish ecology are intertwined in the complex suite of biotic and abiotic characteristics that structure aquatic ecosystems and are highly site-, species-, and life stage-specific. Assessments of the impact of SDFV on fish ecology should first characterize local habitat and channel quality and fish community composition to identify specific, measurable ecological outcomes to sustain or enhance, and then design mitigation strategies tailored to those ecological objectives.

13 HYDRO ENERGY↗
DOE OSTI2025

Methods to Observe Tribological Failures in Self-Mated Steel Contacts

Scuffing, a type of wear found in highly stressed or poorly lubricated contacts, is characterized by a rapid increase in friction and severe plastic deformation of the near-surface material. Scuffing has proven difficult to study because it initiates unpredictably, progresses rapidly, and typically develops within an inaccessible contact interface. Although there have been successful in-situ studies of scuffing in real-time, the transparent counter body needed for these studies changes the interactions between the surfaces and the lubricant, which affects the scuffing process in unknown ways. This paper describes the development of X-ray-compatible tribometry to study the scuffing of self-mated steels in-situ and in real-time. The method uses a crossed cylinders configuration with a thin (500 μm thick) stationary component and a small (≈200 μm) contact width to maximize X-ray interactions with atoms within the stress field generated by the contact. The resulting instrument and method are used to benchmark the scuffing response of self-mated 52,100 steel under tribologically challenging ‘oil-off’ lubrication conditions. The results demonstrate reliable scuffing in this configuration despite the relatively small contact areas and loads used. Following scuffing, gross plastic deformation was observed on both surfaces along with significant subsurface grain refinement and flow only on the stationary surface, which experienced constant contact. Interestingly, high friction initiated at specific locations of the migratory surface, which experienced intermittent contact, and then propagated across the track over time, suggesting that local conditions of the migratory surface dominated friction leading into the failure event.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Accumulative Roll Bonding of Alloy 2205 Duplex Steel and the Accompanying Impacts on Microstructure, Texture, and Mechanical Properties

The mechanical and microstructural evolution of Alloy 2205 during severe plastic deformation is examined in this study. A combination of accumulative roll bonding (ARB) and cold rolling results in the successful formation of a nanograined dual-phase microstructure of austenite and ferrite with some transformed martensite. Severe deformation to cumulative reductions of 80.5, 92.5, 95, and 97 pct were performed. Microscopy indicates that grain dimensions in the sheet normal direction is less than 100 nm for reductions ≥ 92.5 pct. Shear banding is observed at reductions ≥ 95 pct while twinning is only observed at reductions < 92.5 pct. Neutron diffraction measurements indicated the presence of martensite for reductions ≥ 95 pct at ~ 8 pct volume fraction. Taken in conjunction, it appears that during initial ARB processing, both slip and twinning are active plastic mechanisms. As twinning becomes exhausted, martensitic transformation, slip, and intermittent shear banding account for the active plasticity mechanisms. Material hardness saturates at 92.5 pct reduction, with a maximum hardness of 45 HRC. Sub-sized tensile testing confirms this approximate hardness with measurements indicating a UTS of ~ 1440 MPa. Texture analysis of crystal orientation distributions in the plate normal direction suggest an approximate Kurdjumov–Sachs orientation relationship at all reductions above 80 pct indicating stability of the orientation relationship at high strains. The intragranular structure develops a fine scale sub-grain content with increasing deformation, resulting in a continual evolution of texture up to and including 97 pct reduction. The final structure presents strong components of Goss and rotated cube texture in both the austenite and ferrite. In this body of work we aim to compare ARB of an industrially relevant FCC/BCC system (Alloy 2205) to historical model FCC/BCC systems such as Cu/Nb.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantifying spatiotemporal variability in occupant exposure to an indoor airborne contaminant with an uncertain source location

Well-mixed zone models are often employed to compute indoor air quality and occupant exposures. While effective, a potential downside to assuming instantaneous, perfect mixing is underpredicting exposures to high intermittent concentrations within a room. When such cases are of concern, more spatially resolved models, like computational-fluid dynamics methods, are used for some or all of the zones. But, these models have higher computational costs and require more input information. A preferred compromise would be to continue with a multi-zone modeling approach for all rooms, but with a better assessment of the spatial variability within a room. Here to do so, we present a quantitative method for estimating a room's spatiotemporal variability, based on influential room parameters. Our proposed method disaggregates variability into the variability in a room's average concentration, and the spatial variability within the room relative to that average. This enables a detailed assessment of how variability in particular room parameters impacts the uncertain occupant exposures. To demonstrate the utility of this method, we simulate contaminant dispersion for a variety of possible source locations. We compute breathing-zone exposure during the releasing (source is active) and decaying (source is removed) periods. Using CFD methods, we found after a 30 minutes release the average standard deviation in the spatial distribution of exposure was approximately 28% of the source average exposure, whereas variability in the different average exposures was lower, only 10% of the total average. We also find that although uncertainty in the source location leads to variability in the average magnitude of transient exposure, it does not have a particularly large influence on the spatial distribution during the decaying period, or on the average contaminant removal rate. By systematically characterizing a room's average concentration, its variability, and the spatial variability within the room important insights can be gained as to how much uncertainty is introduced into occupant exposure predictions by assuming a uniform in-room contaminant concentration. We discuss how the results of these characterizations can improve our understanding of the uncertainty in occupant exposures relative to well-mixed models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Evaluating indoor thermal resilience of passive and low-power cooling shelters for outdoor workers in India

India’s 231 million outdoor workers are exposed to deadly heat during heat waves. We report results from a simulation-based study that focuses on passive design of cooling shelters for the hot and dry climate zone of India. The goal is to design a cooler-than-outdoor shelter for outdoor workers’ intermittent rest and recovery from heat stress during their arduous outdoor work, to avoid heat-related morbidities and mortality. Expected indoor thermal conditions in low-cost cooling shelters deploying a range of passive designs and low-power active measures are investigated, consistent with the current Indian standards and practices, located in the city of Jodhpur in western India. Heat resilience of the shelter was measured with the predicted reduction of hazardous hours inside the shelter based on the wet-bulb globe temperature (WBGT) and extended heat index. These measures include improving the building envelope, installing cool roofs, using internal thermal mass, and natural ventilation. Additionally, a low-power active measure of using ventilation fans and ceiling fans is explored. EnergyPlus-based simulation results show that simple, commonly available measures, particularly natural ventilation and ceiling fans, achieve the most significant reductions in overheating danger hours, by 22% and 21%, respectively, while more complex or costly passive strategies yield only marginal additional benefits. Moreover, combined measure packages are identified that can reduce the indoor WBGT by 8 to 10 °C, eliminating overheating danger hours. These findings highlight the critical importance of scalable, low-cost, and easily deployable cooling solutions for developing resilient cooling shelters for vulnerable outdoor workers during heat waves in India.

building performance↗
DOE OSTI2020

3D printing of metal-based materials for renewable energy applications

Large-scale renewable energy must overcome conversion and storage challenges before it can replace fossil fuels due to its intermittent nature. However, current sustainable energy devices still suffer from high cost, low efficiency, and poor service life problems. Recently, porous metal-based materials have been widely used as desirable cross-functional platforms for electrochemical and photochemical energy systems for their unique electrical conductivity, catalytic activity, and chemical stability. To tailor the porosity length scale, ordering, and compositions, 3D printing has been applied as a disruptive manufacturing revolution to create complex architected components by directly joining sequential layers into designed structures. In conclusion, this article intends to summarize cutting-edge advances of metal-based materials for renewable energy devices (e.g., fuel cells, solar cells, supercapacitors, and batteries) over the past decade.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Transforming nanoscale VO 2 (B) into a scalable sodium-ion electrode

The intermittent nature of renewable energies requires highly reliable grid-level energy storage approaches. A critical consideration in developing this technology is the areal capacity which determines battery performance and influences the cost of battery technology. Of related importance is finding new ways of developing scalable electrodes. In recent years, three-dimensional (3D) printing of conductive scaffolds has emerged as an alternative to overcome the scalability limitations of commercial tape cast electrodes. The research carried out in the current study demonstrates a successful scalability pathway for nanoscale VO 2 (B), a desirable cathode for sodium-ion batteries which has a nano-flower morphology with a crystallite size < 20 nm. By electrodepositing VO 2 (B) onto a graphene aerogel scaffold, we were able to achieve mass loading of over 100 mg·cm −2 and still possess an areal capacity of 10 mAh·cm −2 at a current density of 5 mA·cm −2 . Moreover, after 1000 cycles, these electrodes retained 75% to 80% of their initial capacity. Even at high loading levels, the electrodeposited VO 2 (B) exhibits pseudocapacitive material signatures such as a box-like voltammetry response, linear galvanostatic response, and no phase change upon lithiation. The scalability of the VO 2 (B) electrode is demonstrated in a series of experiments which show the areal capacity to scale upon increase in both mass loading and electrode thickness, with only small changes in specific capacity. Furthermore, this study establishes that nanoscale materials can be scaled up to achieve thick electrodes without compromising their electrochemical properties.

additive manufacturing↗
DOE OSTI2021

Understanding the Value of Energy Storage for Power System Reliability and Resilience Applications

Abstract Purpose of Review The need for energy storage in the electrical grid has grown in recent years in response to a reduced reliance on fossil fuel baseload power, added intermittent renewable investment, and expanded adoption of distributed energy resources. While the methods and models for valuing storage use cases have advanced significantly in recent years, the value of enhanced resilience remains an open research question. Recent Findings The findings of the recent research indicate that energy storage provides significant value to the grid, with median benefit values for specific use cases ranging from under $10/kW-year for voltage support to roughly $100/kW-year for capacity and frequency regulation services. While the value of lost load is used widely to estimate the benefits of mitigating short-duration outages, reaching as high as $719/kilowatt-year, there is no consensus when it comes to monetizing the value of improving grid resilience. Summary This paper presents a use case taxonomy for energy storage and uses the taxonomy to conduct a meta-analysis of an extensive set of energy storage valuation studies. It reviews several approaches for monetizing reliability and resiliency services and presents a proposed approach for valuing resiliency for energy storage investments.

25 ENERGY STORAGE↗
DOE OSTI2021

Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.

Li, H↗
DOE OSTI2023

Advances in solar forecasting: Computer vision with deep learning

Renewable energy forecasting is crucial for integrating variable energy sources into the grid. It allows power systems to address the intermittency of the energy supply at different spatiotemporal scales. To anticipate the future impact of cloud displacements on the energy generated by solar facilities, conventional modeling methods rely on numerical weather prediction or physical models, which have difficulties in assimilating cloud information and learning systematic biases. Augmenting computer vision with machine learning overcomes some of these limitations by fusing real-time cloud cover observations with surface measurements acquired from multiple sources. This Review summarizes recent progress in solar forecasting from multisensor Earth observations with a focus on deep learning, which provides the necessary theoretical framework to develop architectures capable of extracting relevant information from data generated by ground-level sky cameras, satellites, weather stations, and sensor networks. Overall, machine learning has the potential to significantly improve the accuracy and robustness of solar energy meteorology; however, more research is necessary to realize this potential and address its limitations.

14 SOLAR ENERGY↗
DOE OSTI2021

Consumable development to tailor residual stress in parts fabricated using directed energy deposition processes

Distortion and residual stresses are major challenges that limit the ability to fabricate large scale structures using Additive Manufacturing (AM). Researchers worldwide are evaluating techniques to induce compressive residual stress in the parts via intermittent rolling. While reasonable success has been documented, the idea of lowering the martensite start temperature to induce compressive stresses has not been evaluated in the context of AM, despite demonstrated success by the welding community. This study validates the hypothesis that, by a proper selection of materials and process parameters, one may effectively reduce distortion and induce a compressive residual stress in AM parts. Using neutron diffraction to measure residual stresses in parts, we demonstrate that, in addition to selection of the correct materials, the inter pass temperature plays a major role in controlling the residual stress evolution. The observations relating to the residual stresses are rationalized based on a microstructural evolution in these samples. Based on this preliminary study, a strategy to fabricate large structures with minimal distortion and residual stress is outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nuclear fuels for transient test reactors

Transient test reactors with the ability to test fissile specimens under extreme conditions have been crucial tools in the development of nuclear technologies. Less than 10 unique facility designs have ever been constructed, most of which remain operational today and still use the original nuclear fuel constructed for them more than 40 years ago. Historic fuel systems for transient test reactors vary in significant ways which have marked influences on reactor capabilities. Eventually, new fuel will be needed to support the longevity of transient test reactor missions. This paper reviews precedent transient reactor fuel systems in the context of their unique requirements. A few key conclusions are illustrated by comparing and contrasting these transient test reactors. Fuel composites which are mostly graphite can enable transient reactors with very high neutron fluence capability (>2E16 n/cm 2 ) and are amenable to longer “shaped” transients but cannot achieve pulses <10 ms in duration. Reducing the graphite-to-uranium ratio can yield a very narrow pulse capability but delivers less fluence and requires cores with considerably more fissile material. Designs based on uranium dioxide (UO 2 ) make use of readily available materials to create compact cores with narrow pulse width capabilities but with moderate neutron fluence capabilities (~2E15 n/cm 2 ). Uranium zirconium hydride (U-ZrHx) is a well-established fuel system for pulsing reactors which has been intermittently manufactured throughout the decades. U-ZrHx offers similar capabilities to UO 2 designs in terms of nuclear kinetics, but with about half the fluence capability (~1E15 n/cm 2 ). An evolution of the UO 2 system, termed “ternary ceramic” fuel, shows that dispersing UO 2 in zirconium oxide and calcium oxide can increase fluence capability greatly (~7E15 n/cm 2 ), but is not presently a commonly available fuel form. A unique composite of UO 2 and beryllium oxide (UO 2 -BeO) can be used to create a core with similar kinetics and compact core geometry as U-ZrHx designs, but with significantly higher fluence capability (~6E15 n/cm 2 ). Like ternary ceramic fuel, newly fabricated UO 2 -BeO would require reestablishing its historic manufacturing process which would be further complicated by the health hazards associated with beryllium. In conclusion, like most engineering problems, there is no perfect solution, but this paper outlines the advantages and disadvantages of candidate fuel options to help guide detailed evaluations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗