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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

NSTX-U research advancing the physics of spherical tokamaks

Abstract The objectives of NSTX-U research are to reinforce the advantages of STs while addressing the challenges. To extend confinement physics of low- A , high beta plasmas to lower collisionality levels, understanding of the transport mechanisms that set confinement performance and pedestal profiles is being advanced through gyrokinetic simulations, reduced model development, and comparison to NSTX experiment, as well as improved simulation of RF heating. To develop stable non-inductive scenarios needed for steady-state operation, various performance-limiting modes of instability were studied, including MHD, tearing modes, and energetic particle instabilities. Predictive tools were developed, covering disruptions, runaway electrons, equilibrium reconstruction, and control tools. To develop power and particle handling techniques to optimize plasma exhaust in high performance scenarios, innovative lithium-based solutions are being developed to handle the very high heat flux levels that the increased heating power and compact geometry of NSTX-U will produce, and will be seen in future STs. Predictive capabilities accounting for plasma phenomena, like edge harmonic oscillations, ELMs, and blobs, are being tested and improved. In these ways, NSTX-U researchers are advancing the physics understanding of ST plasmas to maximize the benefit that will be gained from further NSTX-U experiments and to increase confidence in projections to future devices.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Time-Constrained Capacitated Vehicle Routing Problem in Urban E-Commerce Delivery

Electric vehicle routing problems can be particularly complex when recharging must be performed mid-route. In some applications, such as e-commerce parcel delivery truck routing, however, mid-route recharging may not be necessary because of constraints on vehicle capacities and the maximum allowed time for delivery. In this study, we develop a mixed-integer optimization model that exactly solves such a time-constrained capacitated vehicle routing problem, especially of interest for e-commerce parcel delivery vehicles. We compare our solution method with an existing metaheuristic and carry out exhaustive case studies considering four U.S. cities—Austin, TX; Bloomington, IL; Chicago, IL; and Detroit, MI—and two vehicle types: conventional vehicles and battery electric vehicles (BEVs). In these studies we examine the impact of vehicle capacity, maximum allowed travel time, service time (dwelling time to physically deliver the parcel), and BEV range on system-level performance metrics, including vehicle miles traveled (VMT). We find that the service time followed by the vehicle capacity plays a key role in the performance of our approach. We assume an 80-mi BEV range as a baseline without mid-route recharging. Our results show that the BEV range has a minimal impact on performance metrics because the VMT per vehicle averages around 72 mi. In a case study for shared-economy parcel deliveries, we observe that VMT could be reduced by 38.8% in Austin if service providers were to operate their distribution centers jointly.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Analysis of Respirator Cartridge Performance Testing on the 702-AZ Primary Exhauster for the Hanford AY/AZ Tank Farms during a Waste-Disturbing Event

Washington River Protection Solutions (WRPS) conducted tests using two types of chemical cartridges for use in air-purifying respirators (APR) to determine the period of time that the cartridges would provide adequate performance1 for APRs used to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPC) from vapors exiting the 702-AZ Primary Exhauster for the Hanford AY-AZ tank farms. Unlike prior cartridge testing on the 702-AZ Primary Exhauster, the recent tests were performed during a waste-disturbing event. The Occupational Safety and Health Administration (OSHA) identifies cartridge testing as a valid approach for establishing a cartridge change schedules. Testing is commonly applied in situations where mixtures of COPCs exist, and where other approaches, such as manufacturer recommendations and modeling, are less reliable. The tests were designed and conducted to assure measurement and/or control of the key variables OSHA identified as important to estimate the cartridge service life, including temperature, humidity, COPC concentration, breathing rate, and cartridge adsorption capacity. Testing was conducted from February 10–11, 2017, on a slipstream from the 702-AZ exhauster fed to a respirator cartridge test stand developed by WRPS in collaboration with HiLine Engineering (Richland, Washington). Multipurpose respirator cartridges, SCOTT 7422-SD1 and SCOTT 7422-SC1 (SCOTT Safety, Monroe, North Carolina), were assessed on separate days. Sample media (sorbent tubes) and canisters (e.g., Summa) sampling were used to collect samples of the vapor stream entering and exiting the respirator cartridge and were subsequently analyzed for COPC concentrations. Pacific Northwest National Laboratory was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and service life.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Respirator Cartridge Performance on Mixed Vapors from Hanford Tank Headspaces and Exhausters - 20427

Between 2016 and 2018, the Hanford Tank Operations Contractor - Washington River Protection Solutions (WRPS) - conducted a series of tests of air-purifying respirator (APR) chemical cartridges commonly used at Hanford tank farms to determine the period of time for which the cartridges would provide adequate performance when used in APRs and powered-air-purifying respirators (PAPRs) to protect workers when exposed to a mixture of vapors exiting tank headspaces. Although cartridge manufacturers provide service life estimating tools for individual chemical compounds, the projected performance of these cartridges on complex vapor mixtures is not available, and the adequacy of APRs for tank farm applications represents an important workforce concern. The Occupational Safety and Health Administration identifies cartridge testing as a valid approach for establishing cartridge service life. The primary function of the WRPS Cartridge Test Program was to obtain objective data to determine service lives for the APR and PAPR cartridges used at Hanford tank farms. WRPS contracted with Pacific Northwest National Laboratory to analyze the test data and offer an independent analysis of and recommendations based on respirator cartridge performance. A total of 28 APR and 10 PAPR cartridge tests were conducted between 2016 and 2018 on 12 different tank headspaces and tank farm exhauster slipstreams. Two APR cartridges from SCOTT (now 3M) and two PAPR cartridges from MSA Safety, Inc. and 3M were evaluated using a cartridge testing system specifically designed to measure and monitor test conditions and sample cartridge inlet and outlet vapor streams for important chemical compounds. Testing focused on analysis of approximately 61 tank vapor chemicals of potential concern (COPCs) that have been previously detected in tank vapors at levels above 10% of their occupational exposure limits (OELs). Each test was conducted over 16 hours of run time. Evidence of chemical breakthrough was assessed by comparing inlet and outlet COPC concentrations over the duration of each test. The breakthrough threshold was normally defined as exceeding 10% of the compounds OEL at the cartridge outlet. Ammonia breakthrough was observed in a majority of the cartridge tests and occurred earlier than breakthrough of any other chemical compound. Several other COPCs did exhibit breakthrough behavior, including mercury, 1,3-butadiene, furan, 2,5 dihydrofuran, and N-nitrosodimethylamine (NDMA), but only in a very limited number of cartridge tests and only after ammonia breakthrough had occurred. In addition, tests results suggest that breakthrough of some of these COPCs may have been affected by competition with and breakthrough of other non-COPC organics, such as ethanol and acetone, with substantially lower toxicological hazard. Comparison of cartridge manufacturers' service life estimates with the experimentally derived breakthrough times indicates that manufacturers' estimates are generally conservative, even in the presence of the complex mixed vapor streams experienced in these tests. With consideration of appropriate safety margins, these results provide valuable insights on cartridge performance to inform industrial hygiene professionals in establishing appropriate cartridge change-out schedules for APR and PAPR use in the Hanford tank farms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Co-Optimization Scheme for Hybrid Electric Vehicles Powertrain and Exhaust Emission Control System Using Future Speed Prediction

Hybrid electric vehicles (HEVs) have been an effective solution for improved vehicle fuel efficiency and reduced emission pollution. In this paper, a co-optimization scheme is proposed to optimize fuel efficiency for HEVs. Here, the proposed optimization scheme uses obtainable future speed prediction as the basis to optimally tune control parameters for the existing powertrain control system. The ramp-up time of the catalyst temperature to reach its light-off level in the exhaust emission system is also considered as an additional optimization constraint to reduce emission. The Toyota Prius Hybrid Simulink model which is an integrated model for a powertrain and exhaust emission system is validated using real data from several real driving cycle scenarios. Then, to simplify the formulation of the proposed algorithm, the model for the optimization for powertrain and exhaust emission systems is represented by a set of equivalent neural network (NN) models learned using the data generated from the well-validated Toyota Prius Hybrid Simulink model. Using NN models, a co-optimization algorithm is established that provides an optimal tuning of some fuel-sensitive powertrain control parameters using future speed prediction, leading to a novel co-optimization algorithm, achieving on average a further 9.22% fuel savings for the Toyota Prius Hybrid Simulink model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Mercury Speciation During Vitrification of LAW

n this work, laboratory and engineering-scale tests were conducted that mimic the reactive environment of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) low activity waste (LAW) melter and off-gas system in order to assess the speciation of mercury at select points in the processing system. The experimental protocols, test equipment, feed materials used, and rationale for testing are detailed in the Test Plan for this work. Particular attention was paid to the amount and speciation of mercury in submerged bed scrubber (SBS) solutions, which are intended to be recycled back to the melter feed at the WTP. Results are presented from detailed mercury analysis of these solutions using Environmental Protection Agency (EPA) Method 1630 and modifications to this method for dimethyl mercury and methyl mercury as well as EPA Method 1631 and modifications to this method for total, dissolved, elemental, suspended, and ionic mercury. Testing was conducted in two separate sets of experiments: (1) One set of tests (crucible-scale furnace tests) that involved heating small batches of mercury-spiked melter feed in crucibles to determine the amount of mercury retained in the glass and the species of mercury in the exhaust gases; (2) A second set of tests (DM10 melter tests) was planned that involved creating LAW melter plenum gas compositions using the DM10 melter system, injecting mercury into the off-gas stream, and passing that stream though a reactor that simulates various plenum gas conditions. Operational issues led to the need to use one of the VSL DM100 melters in place of the planned DM10 melter for these tests. The speciation of mercury after exposure to those conditions was monitored. In both sets of tests, the exhaust gases were run through a scrubber that was intended to mimic the LAW SBS in order to determine how much of the mercury exiting the melter would be retained in the primary off-gas system fluids and in what form. After passing through the SBS, the exhaust stream was analyzed to determine particulate, ionic, elemental, and total mercury passing downstream of the SBS. In tests employing gases derived from the DM100 melter that were spiked with elemental mercury, the processing system provided gas temperatures and residence times that are representative of the WTP LAW vitrification system in order to assess the effect of those conditions on mercury speciation. The Decontamination Factor (DF) across the system in the tests with mercury-spiked DM100 melter exhaust was determined using the analytical data from EPA Method 30B (Fluegas Adsorption Mercury Speciation (FAMS TM )) exhaust samples and the amount of mercury detected in the SBS solutions. Mercury species used in melter feed crucible scale tests were divalent (chloride and iodide), monovalent (chloride and fluoride), and elemental mercury. Individual tests included only a single form of mercury in the feed. The results for total mercury mass balances in the crucible tests are also presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Computational modeling predicts the stability of both Pd + and Pd2 + ion-exchanged into H-CHA

Passive NO x adsorbers (PNA) using Pd/zeolites have emerged as a promising solution for the reduction of cold-start emissions from vehicle exhaust. However, the nature of the active sites and the mechanisms underlying NO x adsorption in Pd/zeolites remain a subject of ongoing investigation. In this study, we employ quantum chemical simulations to investigate the structure of Pd species in cation-exchange sites at isolated Al and Al pairs in the 6-ring and 8-ring of the CHA framework before the introduction of NO x . Our calculations show that the speciation of Pd in these exchange sites strongly depends on the precise Al arrangement within the framework, as well as the operating conditions. Ionically dispersed Pd is found to be the most favorable species over a wide range of oxidizing and reducing conditions. Small oligomers of PdO and metallic Pd do not appear to be competitive at either isolated Al or Al pairs. Notably, our calculations show that ion exchange sites other than next–next–nearest neighbor Al pairs in the 6-ring will be preferentially occupied by Pd + instead of Pd 2+ . The stability of Pd + in the zeolite environment is an interesting contrast with its rareness in molecular Pd compounds. Nonetheless, a detailed analysis of the electronic structure shows that predicted Pd oxidation states are consistent with chemical intuition for all complexes investigated in this study. We also discuss the potential ambiguity in Pd characterization provided by typical experimental techniques such as XANES, EXAFS and UV-Vis, and highlight the need for additional EPR spectroscopy studies to further elucidate the initial Pd speciation in zeolites for PNA applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Similarity Downselection: Finding the n Most Dissimilar Molecular Conformers for Reference-Free Metabolomics

Computational methods for creating in silico libraries of molecular descriptors (e.g., collision cross sections) are becoming increasingly prevalent due to the limited number of authentic reference materials available for traditional library building. These so-called “reference-free metabolomics” methods require sampling sets of molecular conformers in order to produce high accuracy property predictions. Due to the computational cost of the subsequent calculations for each conformer, there is a need to sample the most relevant subset and avoid repeating calculations on conformers that are nearly identical. The goal of this study is to introduce a heuristic method of finding the most dissimilar conformers from a larger population in order to help speed up reference-free calculation methods and maintain a high property prediction accuracy. Finding the set of the n items most dissimilar from each other out of a larger population becomes increasingly difficult and computationally expensive as either n or the population size grows large. Because there exists a pairwise relationship between each item and all other items in the population, finding the set of the n most dissimilar items is different than simply sorting an array of numbers. For instance, if you have a set of the most dissimilar n = 4 items, one or more of the items from n = 4 might not be in the set n = 5. An exact solution would have to search all possible combinations of size n in the population exhaustively. We present an open-source software called similarity downselection (SDS), written in Python and freely available on GitHub. SDS implements a heuristic algorithm for quickly finding the approximate set(s) of the n most dissimilar items. We benchmark SDS against a Monte Carlo method, which attempts to find the exact solution through repeated random sampling. We show that for SDS to find the set of n most dissimilar conformers, our method is not only orders of magnitude faster, but it is also more accurate than running Monte Carlo for 1,000,000 iterations, each searching for set sizes n = 3–7 out of a population of 50,000. We also benchmark SDS against the exact solution for example small populations, showing that SDS produces a solution close to the exact solution in these instances. Using theoretical approaches, we also demonstrate the constraints of the greedy algorithm and its efficacy as a ratio to the exact solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

How Atomic Bonding Plays the Hardness Behavior in the Al–Co–Cr–Cu–Fe–Ni High Entropy Family

A systematic study on a face-centered cubic-based compositionally complex alloy system Al–Co–Cr–Cu–Fe–Ni in its single-phase state is carried out, where a mother senary compound Al 8 Co 17 Cr 17 Cu 8 Fe 17 Ni 33 and five of its suballoys, obtained by removing one element at a time, are investigated and exhaustively analyzed determining the contribution of each alloying element in the solid solution. The senary and the quinaries are compared using experimental techniques including X-ray absorption spectroscopy, X-ray diffraction, transmission electron microscopy, and first principles hybrid Monte Carlo/molecular dynamics simulations. Chemical short-range order and bond length distances have been determined both at the experimental and computational level. Electronic structure and local atomic distortions up to 5.2 Å have been correlated to the microhardness values. A linear regression model connecting hardness with local lattice distortions is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Leveraging Hydropower Multi-Sensor Data for Inference and Age-Informed Modeling

Increased demand of operational flexibility such as faster ramp up/down in generation, and more frequent start/stops are putting hydropower plants and their associated components in unprecedented stress. Consequently, these plants are at the high risk of extended and more frequent outage to accommodate unscheduled, and unexpected maintenance. Therefore, hydropower plants are in critical need of data driven and age-informed analysis for their regular and unscheduled operation. Yet not all hydropower plants are exhaustively equipped with sensors and/or measurement streams for their respective components – demanding solutions on how to detect, identify, and locate the cause of any event from the unobservable. Idaho National Laboratory (INL) analyzed the anonymized measurements and event records from the Hydropower Research Institute (HRI) to address this issue, as part of the Water Power Technologies Office (WPTO) funded one year multi-lab project. First, we investigated how time series of multiple sensor measurements can be leveraged to identify an event “root cause” as well as to develop an inference (i.e., estimate the unobservable) problem. INL also investigated how individual hydropower components’ reaction or response times vary across the pre-event, during event, and post-event conditions – enabling the hydropower dynamic models to be age-informed. Finally, the impact of clustering multi-sensor time series on short-term vibration prediction is analyzed. INL will present key findings from these analyses and recommend next steps for stakeholder adoption.

13 HYDRO ENERGY↗
DOE OSTI2020

Performance assessment of long-legged tightly-baffled divertor geometries in the ARC reactor concept

Extremely intense power exhaust channels are projected for tokamak-based fusion power reactors; a means to handle them remains to be demonstrated. Advanced divertor configurations have been proposed as potential solutions. Recent modelling of tightly baffled, long-legged divertor geometries for the divertor test tokamak concept, ADX, has shown that these concepts may access passively stable, fully detached regimes over a broad range of parameters. The question remains as to how such divertors may perform in a reactor setting. To explore this, numerical simulations are performed with UEDGE for the long-legged divertor geometry proposed for the ARC pilot plant conceptual design - a device with projected heat flux power width (λq||) of 0.4 mm and power exhaust of 93 MW - first for a simplified Super-X divertor configuration (SXD) and then for the actual X-point target divertor (XPTD) being proposed. It is found that the SXD, combined with 0.5% fixed-fraction neon impurity concentration, can produce passively stable, detached divertor regimes for power exhausts in the range of 80-108 MW - fully accommodating ARC's power exhaust. The XPTD configuration is found to reduce the strike-point temperature by a factor of ~10 compared to the SXD for small separations (~1.4λq||) between main and divertor X-point magnetic flux surfaces. Even greater potential reductions are identified for reducing separations to ~1λq|| or less. The power handling response is found to be insensitive to the level of cross-field convective or diffusive transport assumed in the divertor leg. By raising the separatrix density by a factor of 1.5, stable fully detached divertor solutions are obtained that fully accommodate the ARC exhaust power without impurity seeding. To our knowledge, this is the first time an impurity-free divertor power handling scenario has been obtained in edge modelling for a tokamak fusion power reactor with λq|| of 0.4 mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Iodine Speciation Effects in LAW Feeds

Tests were conducted on a DM10 vitrification system with prototypical off-gas treatment system, which includes an SBS, WESP, and evaporator based on the design of the evaporator to be installed at the WTP for concentration of the liquid effluents. This allowed determination of the partitioning and speciation of iodine between the melter and the off gas system components, including liquid effluents from the SBS and WESP as well as in the evaporator condensate and concentrate. Evaporator testing was decoupled from melter testing to permit filtration and pH adjustments of process solutions prior to evaporation. In addition, a slip stream was pulled from the exhaust downstream of the WESP and High-Efficiency Particulate Air (HEPA) filters and passed through a caustic scrubber simulating the WTP caustic scrubber to assess iodine partitioning to the caustic scrubber liquid effluent. The tests were conducted using simulated Hanford LAW from tank AP-107, which is the planned first feed for Direct Feed LAW (DFLAW) operations, at a nominal feed concentration of 5.6 molar Na over about 120 hours of testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

IDENTIFICATION OF ADSORBA TION OF ADSORBATE FT-IR BANDS USING IN-SI -IR BANDS USING IN-SITU TECHNIQUES: Pd SPECIATION AND ADSORPTION CHEMISTRY OF Pd-ZEOLITES FOR PASSIVE NOx ADSORPTION

To meet increasingly stringent automotive emissions standards, further improvements in catalytic converter design are necessary. Current automotive catalyst systems are effective at eliminating emission of nitrogen oxides (NOx) once the catalyst reaches operational temperature (~200 °C). NOx emitted at lower catalyst temperatures now comprises most of the NOx released during a typical test cycle. Referred to as “the cold start problem” this issue has come to the forefront of automotive catalyst development, as mitigating these emissions is necessary to further reduce automotive emissions. Passive NOx adsorbers present an appealing solution to the cold start problem, these being a class of materials that chemisorb exhaust components such as NOx, carbon monoxide (CO) and hydrocarbons at near-ambient temperatures, and then desorb these compounds once the downstream catalyst has reached operational temperature. An effective passive NOx adsorber must have several properties: high NOx adsorption at near-ambient temperatures, near-complete NOx desorption at temperatures within the operational range, high thermal stability, and resistance to automotive exhaust components at high temperatures. The potential environmental impact of such a system is substantial, as NOx emissions currently result in the formation of millions of tons of smog and acid rain each year. Pd-exchanged zeolites have shown promise for deployment as Passive NOx adsorbers, though much remains to be understood about their adsorption chemistry and deactivation. In-situ Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) provides a convenient probe of adsorbed species, most automotive exhaust components possessing IR-active chemical bonds. By examining the evolution of IR bands under various pretreatments and adsorbates, the overall Pd-speciation and adsorptive zeolite sites of each material can be characterized, and the identities of IR bands can be deduced. In this work, microreactor-MS analysis of the adsorption and desorption behavior of these materials was also examined, these results being coupled with in-situ DRIFTS temperature programmed desorption (TPD) to correlate desorption events with specific adsorbed species. A pair of zeolite frameworks of similar Si/Al ratio but differing pore size were examined, Beta zeolite (BEA) and Chabazite (CHA) representing a medium- and small-pore framework, respectively. The effect of Pd-loading on BEA was examined, as well as the various deactivation pathways and active sites of each material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

DeepGrid: Robust Deep Reinforcement Learning-based Contingency Management

Increasing uncertainty raised by the integration of renewable energy resources requires an enormous number of simulations to be carried out for the security assessment of the power grid. However, it is challenging to assess the steady-state and dynamic security indices for different system contingency events by doing an exhaustive analysis in real-time due to the computational and communication constraints. One promising solution is using data-driven techniques along with the system models to train an intelligent contingency management framework to better handle the contingencies in real-time. Nevertheless, implementing a data-driven technique to obtain the best remedial actions necessitates to account for the effect of the measurement noise on the performance of the contingency management. To tackle these challenges, we leverage a robust deep reinforcement learning (DRL) algorithm called Double Deep Q-Network (DDQN) to design a recommender system capable of prescribing optimal control actions with the help of the real-time digital simulator (RTDS). The use of RTDS system in combination with the advanced DRL algorithm allows to explore a wide variety of system contingencies in order to derive better remedial actions. The performance of the proposed algorithm is evaluated in IEEE 9-bus system under different loading conditions, and different network configurations in presence of noisy measurements.

Ghasemkhani, Amir↗
DOE OSTI2025

End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment

X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. As X-ray free electron laser (XFEL) facilities advance toward MHz data rates (1 million images per second), traditional peak finding algorithms that require manual parameter tuning or exhaustive grid searches across multiple experiments become increasingly impractical. While deep learning approaches offer promising solutions, their deployment in high-throughput environments presents significant challenges in automated dataset labeling, model scalability, edge deployment efficiency, and distributed inference capabilities. We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. Using this integrated approach, our pipeline achieves accuracy comparable to traditional methods tuned by human experts while eliminating the need for experiment-specific parameter tuning. Although current throughput requires optimization for MHz facilities, our system's scalable architecture and demonstrated model compression capabilities provide a foundation for future high-throughput XFEL deployments.

Wang, Cong↗
DOE OSTI2020

Supercritical Reforming of Wet Ethanol for High Efficiency Direct-injection Heavy-duty Compression-ignition Engines

The purpose of the research was to investigate the potential of using a mature bio-fuel in heavy-duty compression ignition engines. By co-optimizing both the fuel characteristics and engine system the potential for a superior outcome was demonstrated. The use of wet bio-ethanol eliminates the majority of the energy intensive distilling and dehydrating fuel production processes, which moves the fuel towards carbon neutral and also lowers the fuel costs. The relatively high water content of the resulting fuel is leveraged in the proposed novel combustion system by incorporating an integrated high efficiency exhaust waste heat recovery system. This results in significantly higher thermal efficiency. In addition the combustion system features low criteria pollutant emissions and the potential to reduce the initial cost of the engine system hardware. Substantial societal benefits are demonstrated through the co-optimization of the fuel and engine system. A computational proof-of-concept study has been performed to demonstrate the potential benefits of a novel wet ethanol heavy-duty compression ignition combustion system featuring integrated exhaust waste heat recovery. A combined in-cylinder closed cycle 3D computational fluid dynamics (CFD) - 1D engine system simulation approach was used. The models were validated to baseline engine data using diesel fuel and then applied to the wet ethanol study. The original concept was to maximize exhaust waste heat recovery through supercritical reforming of the wet ethanol fuel. Phase I simulation results indicated that the optimal solution for maximum engine efficiency gains were realized through maximizing thermo-mechanical recuperation with negligible fuel reformation. The results show the potential to achieve impressive gains in brake thermal efficiency (BTE) over the base diesel engine. The potential to increase BTE up to 20.9% over the base diesel engine was demonstrated, with even larger gains possible through reduced in-cylinder heat transfer losses. The majority of the efficiency gains were realized through integrated high efficiency exhaust waste heat recovery. The concept also has the potential to achieve future ultra-low NO x emissions standards and negligible engine-out soot emissions. The mixing controlled combustion of high temperature wet ethanol features relatively low engine-out NO x emissions without the need for exhaust gas recirculation (EGR). The soot free combustion enabled by the relatively high oxygen content of ethanol also allows for the use of stoichiometric mixing controlled combustion, which is not practical with diesel fuel. When stoichiometric combustion is used a simple passive 3-way catalyst can be used for exhaust emissions after-treatment and near zero tailpipe emissions. The Phase I simulations results have defined the system layout and requirements in preparation for the Phase II experimental proof-of-concept study. The potential applications of the research include most current applications of diesel engines. The Phase I study focused on heavy-duty on-highway class 8 trucks. However, virtually any application that requires highly efficient clean power generation would benefit from the novel engine system proposed. The results indicate substantial fuel cost savings and reduced greenhouse gas emissions with similar or reduced initial system hardware costs compared to modern diesel engine systems.

09 BIOMASS FUELS↗
DOE OSTI2025

Cooperative Role of Mixed Solvent in the Evaporation-Induced Self-Assembly of Polypeptoid Nanocrystals

Peptoids, or polypeptoids, are biomimetic polymers that can self-assemble into nanocrystals for biomedical and biotechnological applications. Polypeptoid nanocrystals can be prepared by evaporation-induced self-assembly, but the roles of solvent components for this process have long been overlooked at the molecular level, leaving a tunable parameter for improving self-assembly protocols. This work utilized molecular dynamics simulations to study the effects of water and the commonly used tetrahydrofuran (THF) on the assembly of nanosheets from molecules of acetylated diblock polypeptoid, poly-(N-decylglycine)-b-poly-(N-2-(2-(2-methoxyethoxy)-ethoxy) ethylglycine), abbreviated as Ac-Ndc10-Nte10. To probe the stages of self-assembly, isolated molecules and preassembled nanofibers/nanosheets were simulated in pure THF, water, and their mixtures, respectively. The assembly energies show that the THF/water mixture has a greater tendency to form nanosheets than pure water. In a THF/water mixture, polypeptoids were found more uncoiled in isolated states, less compact in disordered agglomerates, and with reduced requirement for the Nte block to cover hydrophobic Ndc surfaces in the nanocrystals. Mixed solvent is vital to initiating self-assembly, as THF assists in the opening of coiled polypeptoid molecules, while water provides the thermodynamics to aggregate and ultimately form nanocrystals. To obtain wider nanosheets, it is recommended that some THF be maintained in the aqueous solvent before it becomes exhausted by evaporation. Near the nanosheet surface, the THF concentration is higher than that in bulk solution (3-4 times in 4 M THF/water). The strong adsorption of THF indicates the self-assembly in a de facto mixed solvent. These results are expected to guide the refinement of evaporation-induced self-assembly protocols for polypeptoid nanocrystals.

Luo, Xubo↗
DOE OSTI2020

Evaluation of H-Canyon Ventilation Exhaust Tunnel Inspection at the Savannah River Site - 20052

The Department of Energy (DOE) H-Canyon Facility at the Savannah River Site (SRS) is operated by Savannah River Nuclear Solutions (SRNS). The Facility Structural Integrity Program [1] provides a process to inspect, evaluate, and document the conditions of passive safety related structural systems and components, their degradation mechanisms and their impact on the safety envelope. The Structural Integrity Program performs periodic visual inspections to confirm the systems and components can perform their safety function and recommend corrective actions before the function is compromised. The H-Canyon Exhaust Tunnel is part of the H-Canyon Ventilation System and is periodically inspected under the Structural Integrity Program. The Tunnel performs a Safety Class passive design feature function that is available 100% of the time. The underground reinforced concrete Tunnel directs Canyon process air from the Canyon to the Sand Filter System. The radiological and chemical airborne activity coupled with the physical configuration of the tunnel precludes a manned entry into the tunnel to perform the inspection. Unlike active systems that can be subjected to physical testing to confirm capability, qualification calculations, including modeling, is performed to assess passive design feature capabilities relative to operational, accident and natural phenomena hazards events. Input for these calculations come from knowledge of field conditions, design drawings and conservative assumptions. The knowledge of field conditions comes from concrete and soil testing activities as well as inspection data. The use of cameras on crawlers to obtain inspection data and how that data is used in qualification calculations is the focus of this discussion. Remote Tunnel inspections have been performed using cameras on a stick, referred to as pole cameras, prior to Calendar Year 2003 (CY2003). Since CY2003, six camera equipped crawlers have been used. Crawlers have evolved and improved by incorporating lessons learned from the previous inspections. The latest 2019 crawler successfully traveled the entire length of the tunnel between the Canyon and Sand Filter System and captured images that were previously unseen, thus providing key visual data for the Structural Integrity Program report [2]. The inspection data serves as 1) input to qualification calculations, 2) validates current conditions remain bounded by qualification calculations, and 3) documents a record of change over time. This data is vital for the effective evaluation of the tunnel structure and aids with predicting the life cycle service life safety envelope to protect the public, environment, and facility worker. The goal of the 2019 deployment was to use a more robust vehicle to ensure travel over obstacles, perform the inspection with higher resolution cameras, and have the ability to elevate the cameras to view surfaces previously obscured by abandon-in-place ducts in the tunnel. The inspection information will serve to strengthen the input basis for qualification calculations, versus using excessive conservative calculation assumptions. This 2019 inspection was compared with previous crawler visual evidence to identify change over time to project remaining service life and confirm field conditions remain bounded by qualification calculations. The results of the 2019 Exhaust Tunnel inspection continue to improve and provide a firm basis to make sound engineering judgements regarding tunnel capability and approaches in projecting remaining service life with an aging system and component. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗