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At least 1,459 records · Page 81

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields, in part due to a culture of open data sharing and reuse. AI/ML methodology is well-suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Casaletto↗

The Temporal and Spatial Development of dB/dt for Substorms

Ground induced currents (GICs) due to space weather are a threat to high voltage power transmission systems. However, knowledge of ground conductivity is the largest source of errors in the determination of GICs. A good proxy for GICs is dB/dt obtained from the Bx and By components of the magnetic field fluctuations. It is known that dB/dt values associated with magnetic storms can reach dangerous levels for power transmission systems. On the other hand, it is not uncommon for dB/dt values associated with substorms to exceed prior Pulkkinen and Molinski critical thresholds of 1.5 nT/s and 5 nT/s, respectively, and the temporal and spatial changes of the dB/dt associated with substorms, unlike storms, are not well understood. Using two dimensional maps of dB/dt over North America and Greenland derived from the spherical elementary currents, we investigate the temporal and spatial change of dB/dt for both a single substorm event and a two dimensional superposed epoch analysis of many substorms. Both the single event and the statistical analysis shows a sudden increase of dB/dt at substorm onset followed by an expansion poleward, westward, and eastward after the onset during the expansion phase. The area of dB/dt values exceeding the two critical thresholds from the initial onset dB/dt values showed little to no expansion equatorward. The temporal and spatial development of the dB/dt resembles the temporal and spatial change of the auroral emissions. Substorm values of dB/dt peak shortly after the auroral onset time and in at least one event exceeded 35 nT/s for a non-storm time substorm. In many of our 81 cases the area that exceeds the threshold of 1.5 nT/s is over several million square kilometers and after about 30 minutes the dB/dt values fall below the threshold level. These results address one of goals of the Space Weather Action Plan, which are to establish benchmarks for space weather events and improve modeling and prediction of their impacts on infrastructure. Plain language: The change in the ground magnetic field with respect to time (dB/dt) associated with magnetic storms (a large disturbance of the magnetic field of the earth) can reach dangerous levels for power transmission systems. On the other hand, substorms, which are a smaller more localized disturbance of the Earth’s magnetic field, are more common. It is not uncommon for substorm dB/dt values to also exceed dangerous levels and the temporal and spatial changes of the dB/dt associated with substorms, unlike storms, are not well understood. Our analysis shows a sudden increase of dB/dt at substorm onset, which peaks shortly after the start of the substorm, followed shortly after by an expansion northward, westward, and eastward after the onset.

ionospheric currents↗

Neural-Based Compression Scheme for Solar Image Data

Studying the solar system and especially the Sun relies on the data gathered daily from space missions. These missions are data-intensive and compressing this data to make them efficiently transferable to the ground station is a twofold decision to make. Stronger compression methods, by distorting the data, can increase data throughput at the cost of accuracy which could affect scientific analysis of the data. On the other hand, preserving subtle details in the compressed data requires a high amount of data to be transferred, reducing the desired gains from compression. In this work, we propose a neural network-based lossy compression method to be used in NASA’s data-intensive imagery missions. We chose NASA’s Solar Dynamics Observatory (SDO) mission which transmits 1.4 terabytes of data each day as a proof of concept for the proposed algorithm. In this work, we propose an adversarially trained neural network, equipped with local and non-local attention modules to capture both the local and global structure of the image resulting in a better trade-off in rate-distortion (RD) compared to conventional hand-engineered codecs. The RD variational autoencoder used in this work is jointly trained with a channel-dependent entropy model as a shared prior between the analysis and synthesis transforms to make the entropy coding of the latent code more effective. We also studied how optimizing perceptual losses could help our neural compressor to preserve high-frequency details of the data in the reconstructed compressed image. Our neural image compression algorithm outperforms currently-in-use and state-of-the-art codecs such as JPEG and JPEG-2000 in terms of the RD performance when compressing extreme-ultraviolet (EUV) data. As a proof of concept for use of this algorithm in SDO data analysis, we have performed coronal hole (CH) detection using our compressed images, and generated consistent segmentations, even at a compression rate of ∼ 0.1 bits per pixel (compared to 8 bits per pixel on the original data) using EUV data from SDO.

Image coding↗

Integrated Waste Trade Study: Lunar Surface to Deep Space

The Logistics Reduction Project is one of NASA's technology development projects that is preparing humanity for deep space missions. Reducing the mass and volume of logistical supplies that must be carried from Earth to support the missions and their crews is the primary goal of the project. Effective ways to achieve this goal include reducing, reusing, or recycling wastes generated throughout the mission. Due to the goal of the project, waste processing technologies were analyzed for Lunar surface missions at various lengths and an 850-day Mars transit mission to evaluate the potential benefits of waste processing pertaining to each mission. The technologies assessed include trash compaction, trash-to-gas and human metabolic waste processing technologies, integrated with the baseline architectures of each mission’s habitat. The fully integrated systems were analyzed using an equivalent system mass, which is a metric that encompasses the mass, volume, power and cooling of a system, resulting in an estimate of launch mass and serving as a proxy for cost. Each system’s equivalent system mass was compared to that of the baseline waste processing system of the respective habitat, hand compaction with storage for Lunar surface missions and hand compaction with jettisoning for Mars transit, to evaluate whether the traded waste processing technology was beneficial. This analysis identifies a general trend that more sophisticated waste processing can be beneficial depending on the mission duration. For Lunar surface missions, the water recovery from waste processing can pay off over consecutive missions, due to offsetting the losses from the system via extravehicular activities. In contrast for Mars transit, the primary objective is mass removal from the spacecraft, so technologies like trash-to-gas are competitive with the baseline. Furthermore, the technologies which can recover resources from waste, such as water, may present additional advantages to an ever-changing Mars mission architecture.

Waste processing↗

Review of melt inclusions in lunar rocks: constraints on melt and mantle composition and magmatic processes

Mineral-hosted melt inclusions provide a window into magmatic processes and pre-eruptive liquid compositions. Because melt inclusions are small (typically < 100 µm), the study of lunar melt inclusions is enabled by advancements of microbeam instrumental techniques. In the 1970s immediately following the Apollo and Luna missions, major and minor oxide concentrations of lunar melt inclusions were measured using electron microprobes. The data were used to understand magma evolution, and they revealed the immiscibility of two silicate liquids in the late stage of lunar magma evolution. More recently, the development of secondary ion mass spectrometry as well as laser ablation–inductively coupled plasma–mass spectrometry has enabled the measurement of key volatile elements and other trace elements in lunar melt inclusions, down to about the 0.1 ppm level. The applications of these instruments have ushered in a new wave of lunar melt inclusion studies. Recent advances have gone hand in hand with improved understanding of post-entrapment loss of volatiles. These studies have provided deep insights into pre-eruptive volatiles in lunar basalts, the abundance of volatiles in the lunar mantle, the isotopic ratios of some volatile elements, and the partition of trace elements between host olivine and melt inclusions. The recent studies of lunar melt inclusions have played a critical role in establishing a new paradigm of a fairly wet Moon with about 100 ppm H2O in the bulk silicate Moon (rather than a “bone-dry” Moon) and have been instrumental in developing an improved understanding of the origin and evolution of the Moon.

Youxue Zhang↗

Filament Wound Composite Analysis Using the NASA Multiscale Analysis Tool (NASMAT) and Finite Element Analysis

Fiber reinforced composite materials, owing to their tailorable thermomechanical and functional properties, allow one to produce a structure that is stronger, stiffer, and lighter than its metal counterpart while performing the same function, yielding a more efficient structure. This not only allows for the improvement of current technologies like aircraft structures, but also enables new technologies like gaseous hydrogen storage for mobility applications, which are otherwise impractical when manufactured using traditional metals due to weight and space restrictions or material embrittlement. However, the use of composites imposes greater design and manufacturing challenges on an engineer, since they are heterogenous, having a distinct structure across multiple length scale, behave generally anisotropically at the structural level and require complex manufacturing and processing methods. Capturing this complex behavior requires detailed numerical simulations, including the modeling of microstructural features like undulations, voids, and fiber alignment. In this paper, multiple repeating unit cells (RUCs), representing filament wound composites, are developed (via a script provided in the Appendix) and analyzed. The refinement of these RUCs is varied, and the analyses are performed using both the Abaqus finite element software and the NASA Multiscale Analysis Tool (NASMAT). A study is undertaken to compare the predicted effective elastic properties of the wound RUC to a laminate representation of the wound RUC, which neglects the undulations. Additionally, two different sets of periodic boundary conditions (PBCs) have been examined. One approximates the real boundary conditions using a standard approach and the other represents the PBCs exactly through the use of an offset. Lastly, a comparison of the local elastic stress fields is made among the models and approaches. Since wound structures are often approximated as laminated structures, it is important to understand the degree to which this assumption is valid, namely by first comparing the elastic constants and local elastic fields. This will provide, on the one hand, information concerning the bulk mechanical behavior and, on the other hand, insights concerning local load distributions and likely damage initiation sites.

Composites↗

Detangling Safety Knowledge with Contextualism

We have contradictory intuitions about knowing that things are safe: on the one hand, we claim to have knowledge that many systems (even complex ones) are safe in ordinary language. On the other hand, when challenged by an expert, we easily admit that we do not, in fact, possess very much safety knowledge at all. This Technical Memorandum (TM) attempts to reconcile these two competing intuitions using a philosophical view called epistemic contextualism. We can use epistemic contextualism to explain the importance of safety regulations and the goal in implementing them: first, to differentiate types of disagreement and establish a common basis upon which regulators and regulatees can know that a system is safe; second, to raise ordinary consumers’ standards for safety knowledge (given adequate knowledge of the comprehensiveness of the regulation). This TM also uses the contextualist framework of relevant alternatives to elucidate types of failure possibilities and explain complications in attempts to prevent common mode failures.

language↗

A phase transition model and temporal logic specifications for smart energy systems - revisited

In this paper, we revisit the method of a phase transition model for representing hybrid systems and temporal logic specifications (TLSs) for specifying desired behaviors of systems, and discuss their usefulness for smart energy systems. On the one hand, the phase transition model incorporates the continuous model of the relay device action with a particular structural form that allows for the construction of a single, global differential-algebraic equation for hybrid systems (thus smoothed hybrid systems). On the other hand, the TLS allows sophisticated descriptions of control specifications addressing both magnitude and time simultaneously, which has recently been applied to the control strategy of several types of continuous and hybrid systems. We provide high-level descriptions of each of the two techniques and present simulation results in the context of smart energy systems.

Park, Byungkwon↗

Multiphysics coupling plan

In this chapter, multiphysics coupling simulations of nuclear reactor systems are reviewed. On the one hand, the mainstream methods of multiphysics coupling are demonstrated. The fundamental theory and coupling scheme of operator splitting methods, Jacobian-free Newton–Krylov methods, and approximate block Newton methods are summarized and presented. On the other hand, some significant works on neutronic and thermal-hydraulic codes coupling, and large research project, including NURESAFE European project, Multiphysics Object-Oriented Simulation Environment plan, and Consortium for the Advanced Simulation of Light Water Reactors project, are reviewed. This chapter helps the readers have a better understanding on the worldwide current status of multiphysics coupling research.

Gui, Miao↗

CSB-RNN: A Faster-Than-Realtime RNN Acceleration Framework with Compressed Structured Blocks

Recurrent Neural Networks (RNN) is widely applied to temporal sequence analysis, where real-time performance is usually in demand. However, RNN suffers a heavy computational workload as the model comes with a large weight matrix. To alleviate the pain, model compression (pruning) schemes have been proposed for RNN that pruning the redundant (near-zero) weight-values. On the one hand, the non-structured pruning methods achieve a considerable pruning rate while bringing the computational irregularity, which is un-friendly to parallel-hardware. On the other hand, the existing structured pruning methods consider the hardware parallelism; However, they suffer a poor pruning rate due to the restrict constraints on pruning structure. This paper presents CSB-RNN, an optimized full-stack RNN framework with the novel compressed structured block (CSB) technique. The CSB-pruned RNN model comes with both fine-granularity that benefits the pruning rate and regular structure that facilitates the hardware-parallelism. Further, we propose a novel hardware architecture for inferencing the CSB-pruned model. Different from conventional parallel hardware, this architecture solves the block-workload imbalance issue and achieves an over 95% hardware utilization. With the experiments on 10 RNN models in 5 application domains, the CSB-RNN realizes 7×-20× lossless compression and up to 50× acceptable lossy-compression, which is 2×-7× to the prior art. With the addition of the novel hardware, the compressed-RNN inference reaches a super real-time latency of 10-400µs with FPGA implementation.

Shi, Runbin↗

xSDK: Building an ecosystem of highly efficient math libraries for exascale

Current efforts to build increasingly powerful computer architectures are opening up new avenues for more complex and higher fidelity simulations coupled with data analytics and learning, leading to new scientific insights and deeper understanding. At one extreme, exascale computers will be much faster than previous computer generations (performing 10 18 operations per second—that is, 1,000 times faster than petascale). To achieve these performance improvements, computer architectures are becoming increasingly complex, with deep memory hierarchies, very high node and core counts, and heterogeneous features such as graphics processing units (GPUs). Such architectural changes impact the full breadth of computing scales, as heterogeneity pervades even current-generation laptops, workstations, and moderate-sized clusters. While emerging advanced architectures provide unprecedented opportunities, they also present significant challenges for developers of scientific applications, such as multiphysics and multiscale codes, who must adapt their software to handle disruptive changes in architectures and new programming models that have not yet stabilized. Developers must consider increasing concurrency while reducing communication and synchronization, and other complexities such as the potential for using mixed precision to leverage the compute power available in low-precision tensor cores. On one hand, developers must implement new scientific capabilities, which in turn increase code complexity. On the other hand, the codes must be ported to new architectures, requiring the inclusion of new programming models and the restructuring of code to achieve good performance. Addressing these issues is beyond the capability of any single person or team—leading to the need for collaboration among many teams, who encapsulate their expertise in reusable software and work together to create sustainable software ecosystems.

97 MATHEMATICS AND COMPUTING↗

Feasibility Study for a Proposed Subcritical Assembly at Oak Ridge National Laboratory

Nuclear Criticality Safety (NCS) staff use the guidelines in the ANSI/ANS-8.26 standard to establish and maintain their training and qualifications. Section 7.4 of the standard requires NCS staff to participate in hands-on experiments meant to “…demonstrate how varying the properties of a fissionable material system can affect neutron multiplication.” This training is performed to ensure NCS and operations staff are aware of the risks involved with conducting operations with fissionable materials outside reactors. A new, inherently safe, subcritical assembly, to be housed at Oak Ridge National Laboratory (ORNL) is being considered to augment the current training capabilities of the US Department of Energy/National Nuclear Security Administration (DOE/NNSA) Nuclear Criticality Safety Program (NCSP), which conducts hands-on subcritical and critical experiments to support the training and qualifications of NCS staff. This paper reports the results of a feasibility study performed by ORNL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Providing Ancillary Services with Photovoltaic Generation in Multi-Timescale Grid Operation: Preprint

With photovoltaic (PV) generation substantially increases, electric power systems need more flexible resources that can provide ancillary services to mitigate the variability and uncertainty of the PV generation. On the one hand, the increase of PV generation necessitates the needs of more flexible resources. On the other hand, PV generation, because of its low operation cost, has been replacing the conventional generation in the system which is the main flexible resources in the current system. Consequently, there is a trend to require the renewable generation including PV to provide flexible ancillary services to further accommodate more PV integration. This paper proposes a multi-timescale grid operation model considering the various control strategies of PV providing different ancillary services. Numerical case studies demonstrate that with PV providing both regulation reserve and primary frequency reserve, the system operating costs and PV curtailment will be reduced significantly. It shows that not only the system reliability but also PV's profitability can be improved with PV providing more ancillary services.

41 EE - Solar Energy Technologies Office (EE-4S)↗

An Optimization-Based Strategy for SAV Fleet Repositioning

With the emergence of autonomous technology, shared autonomous vehicles (SAVs) will potentially be the prevalent transportation mode for urban mobility. On one hand, relying on SAV fleets can provide several operational benefits. On the other hand, SAVs can increase travel distance and add congestion due to unoccupied trips such as pickup and repositioning trips. One important aspect for a SAV fleet's success is to serve the incoming requests at reasonably low waiting time. This is achieved by an adequate fleet size that is spatially distributed thoughtfully so that incoming requests can be served by a nearby vehicle. Unfortunately, it is challenging to keep a satisfactory spatial distribution of vehicles due to imbalances in the origin and destination patterns of incoming requests. This paper focuses on the impact of SAV relocation on traveler wait times using a novel optimization-based algorithm for repositioning. POLARIS, an agent-based tool, is used for a case study of Bloomington, Illinois to quantify the benefits of allowing SAV repositioning. On average, the wait times were around 20% lower with repositioning for all adequate fleet sizes. SAVs were available more uniformly across the region's zones, and proportional to trip-making at different times of day. In addition, enabling repositioning led to a higher share of demands being served. These benefits, however, are achieved at the expense of 6% added vehicles miles traveled.

Agent-Based Simulation↗

Alaska's First Thermalize Campaign: An Effort to Reduce Fuel Reliance in Juneau, AK

In 2018, the Bureau and City of Juneau set the goal of reaching 80% renewable energy in the sectors of transportation and space heating by 2045. This effort will minimize their reliance on fossil fuels, reduce their carbon footprint and increase their resilience in the event of a natural disaster as fuel oil reaches Juneau by boat and such shipments may be disrupted in a disaster. The community's resilience in the face of a disaster and lower carbon footprint goes hand-in-hand with public safety and health. The Cold Climate Housing and Research Center (CCHRC) partnered with several local and statewide groups, including Alaska Heat Smart and Information Insights, Inc, to lead Alaska's first thermalize campaign. Thermalize Juneau 2021 is an energy campaign working to lower the cost of heating homes in Juneau through beneficial electrification and increased energy efficiency. The goal of the campaign was to offer homeowners a streamlined and more affordable way to install heat pumps and energy efficiency improvements into their homes. Converting household heating from fuel to electricity also helps improve indoor and outdoor air quality and reduces maintenance requirements. The campaign had over 160 participants. As of Fall 2021, it is in its final stages of heat pump installations and energy efficiency improvements. In addition to tracking the energy savings and carbon reduction attributed to the campaign, the social equity was an important aspect. Thermalize Juneau attempted to include all the demographics present in Juneau in the campaign. The presentation will cover the goals and implementation of the campaign, current data on how it is improving community and household resilience, lessons learned, and next steps.

clean energy↗

Snowmass2021 Cosmic Frontier White Paper: Calibrations and backgrounds for dark matter direct detection

Future dark matter direct detection experiments will reach unprecedented levels of sensitivity. Achieving this sensitivity will require more precise models of signal and background rates in future detectors. Improving the precision of signal and background modeling goes hand-in-hand with novel calibration techniques that can probe rare processes and lower threshold detector response. The goal of this white paper is to outline community needs to meet the background and calibration requirements of next-generation dark matter direct detection experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Study on Emulsification/Demulsification Behavior and Mechanism of Produced Liquid from Polymer Flooding on Alaska North Slope

Heavy oil reservoirs on Alaska North Slope (ANS) are unconsolidated and contain abundant clay minerals, where the first-ever field pilot is currently implemented to validate the use of polymer floods for heavy oil enhanced oil recovery (EOR). The polymer molecules and/or fine clay particles carried with the produced liquid could potentially affect the oil/water separation, which is one of the major concerns for field operators. This dissertation aims to investigate the emulsification behavior of produced liquid, understand the emulsifying mechanism, and seek an adaptive and cost-effective method to treat the produced liquid from polymer flooding. Emulsions were prepared by mechanically mixing the actual heavy oil and the produced water from the pilot site, of which the stability was investigated by bottle test method or multiple light scattering method. Drop size distribution and interfacial properties were measured via microscope and pendant drop technique to probe the stability mechanism further. Results showed that oil-continuous or water-continuous emulsion could be generated depending on the water cut, clay types, clay concentration, and polymer concentration. In the crude oil/water system, the increasing water cut triggered the phase inversion of oil-continuous emulsion to water-continuous emulsion, resulting in faster separation and lower emulsion stability. Whereas, clay particles, no matter added to the oil or water phase, resulted in an unfavorable phase inversion from the loose water-continuous emulsion to the tight oil-continuous emulsion as clay concentration increased. For all four types of clay except Ca-montmorillonite, clay particles added to water led to an earlier phase inversion and higher emulsion stability than that added to the oil. The dual function of polymer on emulsion stability was observed. On the one hand, both sheared and unsheared polymer tended to convert the oil-continuous emulsion formed in either crude oil/water system or complex crude oil/water/clay particle system to the water-continuous emulsion, acting as a weak demulsifier to accelerate the oil/water separation. On the other hand, the addition of polymer to the water-continuous emulsion could result in enhanced emulsion stability, which is primarily attributed to the increased viscosity of the continuous phase and the decreased drop size of the dispersed oil phase. Particularly, the sheared polymer had a weaker ability to stabilize the o/w emulsion than the unsheared polymer due to the lower viscosity of the sheared polymer solution resulting from the breakdown of the polymer macromolecules. As for the chemical demulsification tests, the performance of demulsifiers showed a complex dependency upon the water cut, the shearing intensity, demulsifier type and dosage, and the polymer concentration. A compound emulsion breaker, E12+E18, exhibited the most satisfactory demulsification performance despite the varied test conditions. For severe water-continuous emulsions that might require a multi-fold dosage of demulsifier, a less expensive electrolyte, KCl, was proposed to be used in combination with demulsifier E12+E18 to improve the demulsification performance. In the proposed demulsifier formula, the effectiveness of the commercial demulsifier relied on its destructive effect on the interfacial film, while the efficacy of KCl was mainly dependent on its viscosity reduction effect on the continuous phase. This dissertation illustrates that intermediate layer elimination and water clarification are the major challenges for produced liquid treatment from polymer flooding. It also provides practical and theoretical guidance in advance for the demulsification strategy of the produced liquid from the ongoing first-ever polymer flooding pilot on ANS.

Chang, Hongli↗

Multiscale Experiments and Multiphysics Simulation of Multiphase Flow for Transportable Small Modular Reactors

A new type of safe, small, transportable nuclear reactor would address the intense and ever-growing global demand for energy produced via a resilient, carbon-free energy source. In this regard, transportable small modular reactors (SMRs) are being designed and developed for electricity generation within small/micro-grid/off-grid isolated systems, as well as for heat generation in industrial/residential applications. These reactors feature the capability to be fully factory fabricated and then directly transported to utilities’ sites as “plug-and-play” systems. Research and development (R&D) programs are underway at Idaho National Laboratory (INL) to successfully design, develop, and demonstrate such safe-by-design mobile reactor technologies, in collaboration with partner organizations. Multiscale experimental facilities and multiphysics simulation tools are required for reactor design verification and validation (V&V), and licensing. These advanced reactors are intended to feature passive safety systems such as passive containment cooling systems (PCCS), which consist of multiphase flows and multispecies distributions. This seminar talk will focus on designing and analyzing transportable SMR PCCS by using multiscale experiments and multiphysics computational fluid dynamics (CFD) simulations to support reactor licensing and safety. The corresponding research challenges are addressed via supportive verification and validation results generated by the models and simulation tools in combination with selective parametric and uncertainty analysis. This solution approach could blaze the trail for commercial adoption of such technologies. The facilities, simulation capabilities, and research opportunities available at INL in regard to such reactors and the integrated energy systems with which they go hand in hand are also discussed briefly, and may spark interest in deeper research as well as new collaborative projects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗