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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Observations of Mantle Seismic Anisotropy Using Array Techniques: Shear-Wave Splitting of Beamformed SmKS Phases

Shear-wave splitting measurements are commonly used to resolve seismic anisotropy in both the upper and lowermost mantle. Typically, such techniques are applied to SmKS phases that have reflected (m-1) times off the underside of the core-mantle boundary before being recorded. Practical constraints for shear-wave splitting studies include the limited number of suitable phases as well as the large fraction of available data discarded because of poor signal-to-noise ratios (SNRs) or large measurement uncertainties. Array techniques such as beamforming are commonly used in observational seismology to enhance SNRs, but have not been applied before to improve SmKS signal strength and coherency for shear wave splitting studies. Here, we investigate how a beamforming methodology, based on slowness and backazimuth vespagrams to determine the most coherent incoming wave direction, can improve shear-wave splitting measurement confidence intervals. Through the analysis of real and synthetic seismograms, we show that (a) the splitting measurements obtained from the beamformed seismograms (beams) reflect an average of the single-station splitting parameters that contribute to the beam; (b) the beams have (on average) more than twice as large SNRs than the single-station seismograms that contribute to the beam; (c) the increased SNRs allow the reliable measurement of shear wave splitting parameters from beams down to average single-station SNRs of 1.3. Beamforming may thus be helpful to more reliably measure splitting due to upper mantle anisotropy. Moreover, here we show that beamforming holds potential to greatly improve detection of lowermost mantle anisotropy by demonstrating differential SKS–SKKS splitting analysis using beamformed USArray data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Locating Operational Events of the Cooling Tower of a Nuclear Reactor with a Very Local Seismic Network

Geolocation of emergent seismic signals is challenging at close distances. Here, we used three-component data from a seismic network and a targeted experiment at a research nuclear reactor to locate seismic sources. Utilizing known events collected during the targeted experiment, we were able to infer source locations with seismic amplitudes and polarization characteristics of the data. Although the resolution of the source location is not perfect, the seismic amplitudes and polarization analysis offer useful constraints. For the known events, the source region inferred with our analysis includes the true source locations. Synthetic tests indicate the resolution is largely due to limited data coverage and measurement uncertainties because the synthetic tests show similar results compared with the field data. We identified the source of the unknown event through spectrum cross correlation between the signals from the known events and an unknown event. Our findings were confirmed by operational staff at the facility. When the propagation medium properties (i.e., seismic velocity and quality factor for attenuation) are known, our analysis can be applied to continuous data from a seismic array to infer both source amplitude and location. If the medium properties are not known, a targeted experiment can be conducted to estimate them.

58 GEOSCIENCES↗
DOE OSTI2026

Engineering Enantiocomplementary Protoglobins for Stereoconvergent Construction of N -Alkylated α-Aminoketones

The synthesis of enantiopure compounds from a mixture of E/Z alkenes represents a notable challenge in synthetic chemistry. While enzymes excel in achieving unparalleled selectivity, their inherent specificity often confines activity to a single stereoisomeric substrate, consequently restricting the overall efficiency of such transformations. Here, we demonstrate that protoglobin-derived hemoproteins can catalyze stereoconvergent intermolecular amination using simple N-alkyl hydroxylamines as nitrene precursors, a transformation which remains elusive in synthetic chemistry. These engineered enzymes process E/Z mixtures of silyl enol ethers, enabling the precise incorporation of N-alkyl amino moieties (−NHAlkyl) into diverse molecular structures (up to 79% yield and 95% ee). Two complementary protoglobin variants were engineered using directed evolution to enable enantiodivergent synthesis of both enantiomers of α-aminoketones. This enzymatic platform achieves stereoconvergent and enantiodivergent transformations, facilitating the conversion of simple chemicals into an array of valuable pharmaceutical compounds featuring aminoketone functionalities.

Alcohols↗
DOE OSTI2022

Miktoarm Star Polymers: Synthesis and Applications

Polymers with precisely controlled structure and function are in high demand across a diverse array of applications spanning the life sciences and nanotechnology. One prototypical example is a class of branched block copolymers known as miktoarm stars (μ-stars), which contain two or more arm compositions connected at a common junction. Miktoarm stars have attracted considerable attention since their physical properties can be different from conventional linear block copolymers. This perspective highlights the latest developments and historical context in the field of miktoarm star polymers, including design strategies, synthetic techniques, and advanced characterization tools used to avoid common preparation pitfalls and tailor properties for emerging applications. Furthermore, our contemporary perspective on μ-star polymers is a resource for inspiring future research into this exciting class of materials at the intersection of chemistry, physics, and advanced technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enzymatic Nitrogen Insertion into Unactivated C–H Bonds

Selective functionalization of aliphatic C–H bonds, ubiquitous in molecular structures, could allow ready access to diverse chemical products. While enzymatic oxygenation of C–H bonds is well established, the analogous enzymatic nitrogen functionalization is still unknown; nature is reliant on pre-oxidized compounds for nitrogen incorporation. Likewise, synthetic methods for selective nitrogen derivatization of unbiased C–H bonds remain elusive. In this work, new-to-nature heme-containing nitrene transferases were used as starting points for the directed evolution of enzymes to selectively aminate and amidate unactivated C(sp3)–H sites. The desymmetrization of methyl- and ethylcyclohexane with divergent site selectivity is offered as demonstration. The evolved enzymes in these lineages are highly promiscuous and show activity towards a wide array of substrates, providing a foundation for further evolution of nitrene transferase function. Computational studies and kinetic isotope effects (KIEs) are consistent with a stepwise radical pathway involving an irreversible, enantiodetermining hydrogen atom transfer (HAT), followed by a lower-barrier diastereoselectivity determining radical rebound step. In-enzyme molecular dynamics (MD) simulations reveal a predominantly hydrophobic pocket with favorable dispersion interactions with the substrate. Here, by offering a direct path from saturated precursors, these enzymes present a new biochemical logic for accessing nitrogen-containing compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Efficient Decision Trees for Tensor Regressions

Here, we proposed the tensor-input tree (TT) method for scalar-on-tensor and tensor-on-tensor regression problems. We first address scalar-on-tensor problem by proposing scalar-output regression tree models whose input variables are tensors (i.e., multi-way arrays). We devised and implemented fast randomized and deterministic algorithms for efficient fitting of scalar-on-tensor trees, making TT competitive against tensor-input GP models (Yu, Li, and Liu; Sun et al.). Based on scalar-on-tensor tree models, we extend our method to tensor-on-tensor problems using additive tree ensemble approaches. Theoretical justification and extensive experiments, including testing robustness to entrywise input tensor noise, are provided on real and synthetic datasets to illustrate the performance of TT. Our implementation is provided at https://github.com/hrluo/TensorDecisionTreeRegressor. Supplementary materials for this article are available online.

Decision tree regressions↗
DOE OSTI2023

Two-dimensional perovskite heterostructures for single crystal semiconductor devices

Two-dimensional (2D) perovskites have gained much attention lately owing to their excellent optoelectronic properties, chemical tunability, and environmental stability. Multiple methods have been devised to synthesize high quality 2D perovskite single crystals, and recent progress in fabricating its heterostructures is notable as well. In particular, with growing interest in 2D van der Waals heterostructures, 2D perovskites have become a strong candidate as a new building block for heterostructures to reveal unique physical properties across different interfaces. Until now, various heterostructure devices of 2D perovskite single crystals with other types of 2D materials such as transition metal dichalcogenides (TMDs) and graphene have been studied, which have shown intriguing results including interlayer excitons and enhanced electronic properties. Here, we introduce various synthetic approaches to realize 2D perovskite single crystals and unique characteristics of their single crystal heterostructures fabricated with precision, possessing sharp interfaces. Moreover, recent studies of semiconductor devices based on 2D perovskite single crystal heterostructures are discussed in-depth. New perspectives to further the horizon in the field of 2D perovskite heterostructures are suggested in this work including the consideration of metal–2D material van der Waals contact, application of dry transfer techniques, electric bias driven ion diffusion studies, and nanocrystal array fabrication. 2D perovskite heterostructure single crystal devices factoring in these novel perspectives will further uncover the true potential of these materials for highly efficient and stable semiconductor devices.

Physics↗
DOE OSTI2021

Fast GPU-Based Generation of Large Graph Networks From Degree Distributions

Synthetically generated, large graph networks serve as useful proxies to real-world networks for many graph-based applications. The ability to generate such networks helps overcome several limitations of real-world networks regarding their number, availability, and access. Here, we present the design, implementation, and performance study of a novel network generator that can produce very large graph networks conforming to any desired degree distribution. The generator is designed and implemented for efficient execution on modern graphics processing units (GPUs). Given an array of desired vertex degrees and number of vertices for each desired degree, our algorithm generates the edges of a random graph that satisfies the input degree distribution. Multiple runtime variants are implemented and tested: 1) a uniform static work assignment using a fixed thread launch scheme, 2) a load-balanced static work assignment also with fixed thread launch but with cost-aware task-to-thread mapping, and 3) a dynamic scheme with multiple GPU kernels asynchronously launched from the CPU. The generation is tested on a range of popular networks such as Twitter and Facebook, representing different scales and skews in degree distributions. Results show that, using our algorithm on a single modern GPU (NVIDIA Volta V100), it is possible to generate large-scale graph networks at rates exceeding 50 billion edges per second for a 69 billion-edge network. GPU profiling confirms high utilization and low branching divergence of our implementation from small to large network sizes. For networks with scattered distributions, we provide a coarsening method that further increases the GPU-based generation speed by up to a factor of 4 on tested input networks with over 45 billion edges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Preliminary design overview and performance assessment of the ITER low-field side reflectometer

The design of the ITER low-field side reflectometer (LFSR) has matured to a complete end-to-end preliminary design. LFSR will supply three key plasma measurements: (1) electron density profile, (2) electron density fluctuations, and (3) poloidal rotation. Simultaneous measurements of the three quantities are enabled by an array of six monostatic antennas which inject from an equatorial port on the outboard side of the ITER vessel. Low-loss transmission lines, consisting of corrugated, overmoded waveguide and miter bends, transmit the 30–165 GHz, O- and X-mode signals to and from the ITER plasma. Integrated transmission-line components serve a range of purposes, such as protection from high-power stray radiofrequency radiation, accommodation of transmission-line displacement, and simultaneous measurement of reference and plasma phases during the discharge. Broadband transmission signals are realized by full-band microwave transceivers combined with quasi-optical multiplexing. A field-programmable gate array (FPGA) processor demodulates the profile reflectometer signals, enabling real-time density profile measurements for plasma control system feedback. A full-scale transmission line test facility provides an integrated environment to assess the performance of critical LFSR components. Theoretical modeling together with insertion loss measurements provide the basis for a comprehensive power budget, which accounts for transmitted output power, transmission-line losses, antenna coupling, and plasma effects. Results indicate that high signal-to-noise ratios are achievable with the current design. A synthetic reflectometer model, using real design parameters and baseline ITER profiles, has been developed to estimate the return signal. With evolving microwave and data acquisition technologies, full-band, ultrafast sweeps (<1 μs) will be realizable for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Reconstructing Richtmyer–Meshkov instabilities from noisy radiographs using low dimensional features and attention-based neural networks

We develop an ML-based approach for density reconstruction based on transformer neural networks. This approach is demonstrated in the setting of ICF-like double shell hydrodynamic simulations wherein the parameters related to material properties and initial conditions are varied. The new method can robustly recover the complex topologies given by the Richtmyer-Meshkoff instability (RMI) from a sequence of hydrodynamic features derived from radiographic images corrupted with blur, scatter, and noise. A noise model is developed to characterize errors in extracting features from synthetic radiographs of the simulated density field. The key component of the network is a transformer encoder that acts on a sequence of features extracted from noisy radiographs. This encoder includes numerous self-attention layers that act to learn temporal dependencies in the input sequences and increase the expressiveness of the model. This approach is shown to exhibit an excellent ability to accurately recover the RMI growth rates, despite the gas-metal interface being greatly obscured by radiographic noise. Our approach can be applied in a broad array of fields involving shock physics and material science.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Localization of infrasonic sources via Bayesian back projection

SUMMARY A Bayesian framework is investigated for event-specific localization of infrasonic sources using back projection ray tracing. Direction-of-arrival information from array-based detection analysis is used to initialize a back projection ray path originating from the detecting array location and quantifying propagation characteristics from hypothetical source locations. The Fisher statistic, computed from the array’s beam coherence, is mapped into uncertainty in the launch angles of the ray path. Auxiliary parameters previously introduced for solving the Transport equation to compute geometric spreading along ray paths are used to map uncertainty in the ray launch angles into spatial and temporal uncertainties in the ray path. An atmospheric ensemble approach is applied to account for atmospheric uncertainty, and the relation between uncertainties in the atmospheric state and confidence in estimated localization are evaluated using several ensembles with specified variances. The method is evaluated using a synthetic event in the western United States constructed via forward propagation simulations as well as a single-station, multi-arrival detection from a surface explosion in the western United States. Localization results using this event-specific approach are more accurate and exhibit improved precision than existing Bayesian localization methods that leverage generalized, pre-computed propagation statistics.

58 GEOSCIENCES↗
DOE OSTI2024

Multi-functional Sorbent Technology (MUST) for the Recovery/Removal of Critical/Heavy Metals from Fossil-Related Wastewater

A collection of remediation and recovery technologies like those predicated on photocatalytic-, electric-, chemical-, membrane-, and adsorptive-based processes currently exists in different stages of development or deployment between these methods of water management. Among these technologies, solid sorbent processes embody an optimal balance between cost-effectiveness, environmental friendliness, and technological maturity. The U.S. Department of Energy’s National Energy Technology Laboratory developed a suit of cross-linked, functionalized silica sorbents tailored to eliminate the most toxic metals regulated by the U.S. Environmental Protection Agency (EPA); critical metals identified by the U.S. Geological Survey (USGS); and harmful organics like the infamous perfluoroalkyl and polyfluoroalkyl substances (PFAS). An array of laboratory and field tests proved that the MUST sorbents removed ppb-level lead from drinking water, selenium from FGD wastewater below EPA limits, aqueous dyes and PFAS; and fractionated low ppm-level critical metals (CM) from AMD and simulated produced water. Proof-of-concept for commercial CM recovery was verified through obtaining milligram-quantities of purified Al solids from a sorbent multi-bed AMD field-site test. Commercial efficacy was further supported by achieving purified fractions of adsorbed Mn upon treating both the AMD and synthetic produced water with the laboratory multi-bed test unit.

Wilfong, Walter C.↗
DOE OSTI2022

Spacer2PAM: A computational framework to guide experimental determination of functional CRISPR-Cas system PAM sequences

Abstract RNA-guided nucleases from CRISPR-Cas systems expand opportunities for precise, targeted genome modification. Endogenous CRISPR-Cas systems in many prokaryotes are attractive to circumvent expression, functionality, and unintended activity hurdles posed by heterologous CRISPR-Cas effectors. However, each CRISPR-Cas system recognizes a unique set of protospacer adjacent motifs (PAMs), which requires identification by extensive screening of randomized DNA libraries. This challenge hinders development of endogenous CRISPR-Cas systems, especially those based on multi-protein effectors and in organisms that are slow-growing or have transformation idiosyncrasies. To address this challenge, we present Spacer2PAM, an easy-to-use, easy-to-interpret R package built to predict and guide experimental determination of functional PAM sequences for any CRISPR-Cas system given its corresponding CRISPR array as input. Spacer2PAM can be used in a ‘Quick’ method to generate a single PAM prediction or in a ‘Comprehensive’ method to inform targeted PAM libraries small enough to screen in difficult to transform organisms. We demonstrate Spacer2PAM by predicting PAM sequences for industrially relevant organisms and experimentally identifying seven PAM sequences that mediate interference from the Spacer2PAM-informed PAM library for the type I-B CRISPR-Cas system from Clostridium autoethanogenum. We anticipate that Spacer2PAM will facilitate the use of endogenous CRISPR-Cas systems for industrial biotechnology and synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Demonstrating Advanced Nuclear Energy Solutions for Net Zero

Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st

08 HYDROGEN↗
DOE OSTI2025

Rewiring Aromatic Compound Consumption: Chromosomal Amplification and Evolution of a Foreign Pathway in Acinetobacter baylyi ADP1

Rational engineering strategies that seek to harness the remarkable diversity of microbial metabolism can be limited by incomplete biological knowledge. As described here, a novel approach to address this challenge involved replacing a native pathway for degrading lignin-derived aromatic compounds via ortho cleavage of protocatechuate in Acinetobacter baylyi ADP1 with a foreign meta-cleavage pathway that uses different enzymes, metabolites, and redox carriers. This alteration may improve lignin valorization and coordinate catabolism with bioproduction strategies. When a 14-kbp region of foreign DNA was inserted in the chromosome, the heterologous genes failed to confer growth on target substrates. Regional gene dosage was increased using a synthetic DNA fragment to promote recombination, and higher copy number enabled growth. During adaptive laboratory evolution, compensatory mutations arose that permit growth with one copy of the foreign genes. This complex metabolic remodeling was accomplished without assumptions about the impediments that initially prevented growth. To understand the changes that emerged, a novel transformation assay identified a combination of mutations sufficient for the new phenotype. Three unexpected changes were revealed: loss of one foreign enzyme, loss of one native enzyme, and loss of a two-component transcriptional regulatory system. This study establishes that large multicopy tandem arrays of poorly adapted pathway genes can confer new functions and improve understanding of metabolism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Demand Response Analysis for Different Residential Personas in a Comfort-Driven Behavioral Context

Low demand response (DR) participation and high program drop-out rates continue to impede DR goals that could save up to $13 billion in annual grid expansion and electricity demand costs. Yet, the literature lacks a thorough understanding of how different residential customer segments enrolled in DR programs respond to utility signals in view of occupant comfort considerations. The objective of this study is to gain a clear understanding of the effects of four different customer personas on residential DR. Given current data limitations, this work developed an array of hypothetical personas with varied priorities, activity levels, and comfort thresholds based on demographic variables that have been found in previous studies to influence energy consumption. A BEopt DR model for a reference residential single-family building located in Colorado was built to isolate the effect of differences in buildings or climate. The results provide useful evidence on how persona-comfort differences lead to significant deviations in DR goals (especially peak demand reduction), ranging from 0.1% to 20%. This work presents a novel framework representing comfort preferences in DR models. The data generated, albeit synthetic, and the results could inform DR program design considerations of how different people respond to different comfort priorities.

BEopt↗
DOE OSTI2023

Orientational Order in Spin-Cast Lead-Iodide Perovskite Nanocrystal Solids

Combined synthetic control over size and composition renders colloidal lead-halide perovskite nanocrystals a tunable platform for high-efficiency optoelectronic applications. However, the properties and operational stability of devices based on nanocrystal solids are often dictated by the method of the evaporation-induced assembly. Ubiquitous slow evaporation techniques can produce highly ordered nanocrystal domains but limit the prospects for scalable fabrication of continuous device layers, calling for investigation of approaches to more rapidly form ordered perovskite nanocrystal solids. Here, we study orientationally ordered lead-iodide perovskite nanocrystal solids prepared by conventional spin coating with molecular additives (excess ligand) to enhance ordering within the arrays. In situ X-ray scattering measurements reveal that orientational ordering occurs rapidly upon solvent removal during spin coating and can be further enhanced by manipulating the spin speed. We vary the additive ligand length and explore trade-offs between ordering and layered perovskite impurity formation. Arrays treated with the intermediate-length octylamine ligand exhibit increased in-plane electronic conductivity, suggesting orientational ordering and internanocrystal electronic coupling can be enhanced by the treatment. In conclusion, these results highlight the prospects of establishing long-range order in lead-halide perovskite nanocrystal solids by using simple and fast coating methods.

14 SOLAR ENERGY↗
DOE OSTI2022

Numerical studies on saturated kink and sawtooth induced fast ion transport in JET ITER-like plasmas

Here, this presentation examines the energetic particle transport induced by saturated kink modes and sawtooth crashes in JET deuterium plasmas. It is known that kink mode-resonant transport and phase-space redistribution from sawtooth crashes can drive strong fast ion transport with dependencies on particle pitch and energy. Measurements with JET's Faraday cup fast ion loss detector array have shown that the internal kink growth phase preceding sawtooth crashes produces substantial fast ion losses. This report will numerically investigate the dominant energetic particle transport mechanism with a detailed examination of the fast ion phase-space dependencies, resonances, orbit topology changes, induced losses, and redistribution associated with the long-lived, resonant, kink mode and non-resonant sawtooth crash. The ORBIT-kick model forms the basis of the transport studies with realistic fast ion distributions produced from TRANSP. A recently created reduced model for sawtooth induced transport is used while the saturated kink modes are modeled with ideal MHD codes. The simulations were further validated against experiment with a newly developed synthetic Faraday cup fast ion loss detector in addition to scintillator probe and neutron measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗