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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
NASA NTRS2008

A Planetary Protection Strategy for the Mars Aerial Regional-Scale Environmental Survey (ARES) Mission Concept

The Aerial Regional-scale Environmental Survey (ARES) is a Mars exploration mission concept designed to send an airplane to fly through the lower atmosphere of Mars, with the goal of taking scientific measurements of the atmosphere, surface, and subsurface phenomenon. ARES was first proposed to the Mars Scout program in December 2002 for a 2007 launch opportunity and was selected to proceed with a Phase A study, step-2 proposal which was submitted in May 2003. ARES was not selected for the Scout mission, but efforts continued on risk reduction of the atmospheric flight system in preparation for the next Mars Scout opportunity in 2006. The ARES concept was again proposed in July 2006 to the Mars Scout program but was not selected to proceed into Phase A. This document describes the Planetary Protection strategy that was developed in ARES Pre Phase-A activities to help identify, early in the design process, certain hardware, assemblies, and/or subsystems that will require unique design considerations based on constraints imposed by Planetary Protection requirements. Had ARES been selected as an exploration project, information in this document would make up the ARES Project Planetary Protection Plan.

Kuhl, Christopher A.↗
NASA NTRS2016

Potential Impact of a US Climate Policy and Air Quality Regulations on Future Air Quality and Climate Change

We have investigated how future air quality and climate change are influenced by the US air quality regulations that existed or were proposed in 2013 and a hypothetical climate mitigation policy that aims to reduce 2050 CO2 emissions to be 50% below 2005 emissions. Using the NASA GISS ModelE2 general circulation model, we look at the impacts for year 2030 and 2055. The US energy-sector emissions are from the GLIMPSE project (GEOS-Chem LIDORT Integrated with MARKAL (MARKet ALlocation) for the Purpose of Scenario Exploration), and other US emissions data sets and the rest of the world emissions data sets are based on the RCP4.5 scenario. The US air quality regulations are projected to have a strong beneficial impact on US air quality and public health in year 2030 and 2055 but result in positive radiative forcing. Under this scenario, no more emission constraints are added after 2020, and the impacts on air quality and climate change are similar between year 2030 and 2055. Surface particulate matter with a diameter smaller than 2.5 micron PM(sub 2:5) is reduced by 2 approximately μg/m(sup -3) on average over the USA, and surface ozone by approximately 8 ppbv. The improved air quality prevents about 91 400 premature deaths in the USA, mainly due to the PM(sub 2:5) reduction approximately (74 200 lives saved). The air quality regulations reduce the light-reflecting aerosols (i.e., sulfate and organic matter) more than the light-absorbing species (i.e., black carbon and ozone), leading to a strong positive radiative forcing (RF) over the USA by both aerosols' direct and indirect forcing: the total RF is approximately 0.04 W m(sup -2) over the globe, and approximately 0.8 W m(sup -2) over the USA. Under the hypothetical climate policy, a future CO2 emissions cut is achieved in part by relying less on coal, and thus SO2 emissions are noticeably reduced. This provides air quality co-benefits, but it could lead to potential climate disbenefits over the USA. In 2055, the US mean total RF is +C02 W m(sup -2) due to positive aerosol direct and indirect forcing, while the global mean total RF is -0.06 W m(sup -2) due to the dominant negative CO2 RF (instantaneous RF). To achieve a regional-scale climate benefit via a climate policy, it is critical (1) to have multinational efforts to reduce greenhouse gas (GHG) emissions and (2) to simultaneously target emission reduction of light-absorbing species (e.g., BC and O3) on top of long-lived species. The latter is very desirable as the resulting climate benefit occurs faster and provides cobenefits to air quality and public health.

Air quality↗
DOE OSTI2024

Safety Basis Compliant Flexible Operations [Capstone Project]

Compliant nuclear operations must be weighed against the radiological risk to the worker, public, and the environment. This project set out to look at one facility at Los Alamos National Laboratory (LANL or the Laboratory) and compare the risk with the operational restrictions associated with the Technical Safety Requirements (TSRs). The hope was to identify controls that could be reduced or simplified while maintaining compliance with 10 CFR 830, Nuclear Safety Management. This would result in increasing facility operational flexibility and efficiency. Controls were identified to be simplified or eliminated based on risk. This identification was initially envisioned from the perspective of reanalysis of the accident and hazard analysis consequences. Additionally, it was envisioned that fire testing could show that the consequences of a fire are not as dramatic as analyzed. Specific facility controls were identified that cause operational inefficiencies. Based on data collection, two controls were identified for further evaluation. The first control was combustible loading within the waste storage buildings, and the second control is related to the seismic power cutoff switch. In evaluating the combustible loading control, the thought is that the fire suppression system (FSS) provides adequate protection and the combustible loading controls do not need elevation to a TSR control. The FSS, along with the Fire Protection Program, would provide protection to prevent a fire from impacting large amounts of stored waste material. The seismic switch was more of a challenge. When reviewing the facility operation, it was determined that the facility does not operate anywhere near the established material-at-risk (MAR – radioactive material) limits. By adjusting these limits, a reduced consequence could be achieved and hence, a significant risk reduction achieved. A new operating mode would be used to achieve this reduction. A reduced MAR limit was successfully used as a test case for snow removal during this project. This project expands on that trial case as related to combustible loading and the seismic power cutoff switch TSRs. This will increase the efficiency of operations with reduced TSR controls while reducing overall facility risk. This is a win-win situation for Triad National Security, LLC (Triad) and the U.S. Department of Energy (DOE). Due to schedule and budgetary constraints, not all envisioned work scope was accomplished. However, it is maintained in this report for future efforts.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2000

Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

Cole, Rod↗
DOE OSTI2026

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Power generation-cooling water Nexus: Impacts of cooling water shortage on power system operation - a simulation case study in Illinois, U.S

Cooling water shortage, frequently attributed to drought and heat waves, poses a significant threat to the operations of thermoelectric power plants and further poses a challenge for the entire power system and environmental stakeholders. Recognizing the critical nexus between power generation and cooling water availability and the potential ability of power generations to adjust generation schedules during cooling water shortages, this paper introduces a security-constrained unit commitment and economic dispatch model considering water-energy nexus. In specific, the model is augmented with a unit-level cooling water requirement (CWR) model and multi-level cooling water availability (CWA) constraints. The unit-level CWR model quantifies the cooling water withdrawal per MWh of power generation, taking into account factors such as thermoelectric generation technologies, cooling system technologies, and environmental parameters. The multi-level CWA constraints incorporate pump-level, plant-level, watershed-level, and forced minimum power constraints, utilizing data derived from actual-based cooling water shortage scenarios. Using a simulation case study in Illinois, United States, this research examines the reliability, economic, and environmental implications of cooling water shortages on power system operations. The results show that Illinois may experience 10-15% daily load curtailment and severe congestion between certain regions from the east to central during cooling water shortages, while once-through and wet-tower units experience a 52% and 17% reduction in power generation. In conclusion, overall cooling water withdrawal decreases by 24-38% as severity intensifies.

Cooling water shortage↗
DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

THE HYDROGEN EPOCH OF REIONIZATION ARRAY DISH. II. CHARACTERIZATION OF SPECTRAL STRUCTURE WITH ELECTROMAGNETIC SIMULATIONS AND ITS SCIENCE IMPLICATIONS

We use time-domain electromagnetic simulations to determine the spectral characteristics of the Hydrogen Epoch of Reionization Arrays (HERA) antenna. These simulations are part of a multi-faceted campaign to determine the effectiveness of the dish’s design for obtaining a detection of redshifted 21 cm emission from the epoch of reionization. Our simulations show the existence of reflections between HERA’s suspended feed and its parabolic dish reflector that fall below -40 dB at 150 ns and, for reasonable impedance matches, have a negligible impact on HERA’s ability to constrain EoR parameters. It follows that despite the reflections they introduce, dishes are effective for increasing the sensitivity of EoR experiments at a relatively low cost. We find that electromagnetic resonances in the HERA feed’s cylindrical skirt, which is intended to reduce cross coupling and beam ellipticity, introduces significant power at large delays (-40 dB at 200 ns), which can lead to some loss of measurable Fourier modes and a modest reduction in sensitivity. Even in the presence of this structure, we find that the spectral response of the antenna is sufficiently smooth for delay filtering to contain foreground emission at line-of-sight wave numbers below k {sub ∥} ≲ 0.2 h Mpc{sup -1}, in the region where the current PAPER experiment operates. Incorporating these results into a Fisher Matrix analysis, we find that the spectral structure observed in our simulations has only a small effect on the tight constraints HERA can achieve on parameters associated with the astrophysics of reionization.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

REIMAGINING HEAT EXCHANGERS FOR NEXT GENERATION ENVIRONMENTAL SYSTEMS

Air-to-refrigerant heat exchangers (HXs) are essential components in space conditioning, refrigeration, and power systems, and recent efforts have focused on making these devices more compact, reducing refrigerant charge and lowering manufacturing costs. Historically, HX innovation has been limited by available computational resources, design tools, and manufacturing constraints. The best available technologies utilize tube-fin and micro- or macro-channel tubes with fins, which are not necessarily the optimal designs achievable with current technology. In this paper, we highlight the latest advancements in air-to-refrigerant HXs, specifically emphasizing innovations achieved through shape and topology optimization. A multi-scale design optimization approach is introduced, alongside similar methods in literature, which enable highly sophisticated shape-optimized tube designs with more than 50% reduction in size and 25% reduction in refrigerant charge, essential for A3 refrigerant charge limit compliance. The frameworks integrate traditional heat and mass transfer science with state-of-the-art machine learning, genetic algorithms, and adjoint algorithms to create novel designs. While many of these innovative designs may not be manufacturable using conventional methods, they allow us explore the boundaries of what is possible. These novel air-to-refrigerant HXs are key enablers for ultra-low-refrigerant charge heat pump and refrigeration systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Nonnegative tensor decomposition with custom clustering for microphase separation of block copolymers

High–dimensional datasets are becoming ubiquitous in many applications and therefore unsupervised tensor methods to interrogate them are needed. Here, we report a new unsupervised machine learning (ML) approach (NTFk) based on nonnegative tensor factorization integrated with a custom k–means clustering. We demonstrate the ability of NTFk to extracting temporal and spatial features of phase separation of copolymers as they are modeled by self–consistent field theory. Microphase separation of block copolymers has been extensively studied both experimentally and theoretically. However, the interpretation of computer simulations and/or experimental data, representing temporal and spatial changes of molecular species concentration is still a challenging task. Thus, extracting the phase diagram from simulations or experimental data as well as the interpretation of data requires discernment of the model/experimental parameters (such as, temperature, concentrations, the number of molecular species and the interaction between species) impact on the microphase separation process. An attractive and unique aspect of the introduced ML method is that it ensures the nonnegativity of the extracted latent features. Nonnegativity is an essential constraint needed to obtain interpretable and sparse latent features that are parts–based representation of the data. The custom clustering in NTFk serves to estimate the number of latent features in the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Loss Minimization With Optimal Power Dispatch in Multi-Frequency HVac Power Systems

Low-frequency high-voltage ac transmission scheme has recently been proposed as an alternative approach for bulk power transmission. This paper proposes a multi-period optimal power flow (OPF) for a multi-frequency HVac transmission system that interconnects both conventional 50/60-Hz and low-frequency grids using back-to-back converters with a centralized control scheme. The OPF objective is to minimize system losses by determining the optimal dispatch for generators, shunt capacitors, and converters. The OPF constraints include the operational constraints of all HVac grid and converter stations. The resulting mixed-integer nonlinear programing problem is solved using a proposed framework based on the predictor-corrector primal-dual interior-point method. The proposed OPF formulation and solution approach are verified using a multi-frequency HVac transmission system that is modified from the IEEE 57-bus system. Here, the results with the optimal dispatch from the proposed method during a simulated day show a significant loss reduction and an improved voltage regulation compared to those when an arbitrary dispatch is chosen.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Transverse momentum spectra and nuclear modification factors of charged particles in pp, p-Pb and Pb-Pb collisions at the LHC

We report the measured transverse momentum ($p_T$) spectra of primary charged particles from pp, p-Pb and Pb-Pb collisions at a center-of-mass energy $\sqrt{s}$$_{NN}$ = 5.02 TeV in the kinematic range of 0.15 < $p_T$ < 50 GeV/$c$ and |$η$| < 0.8. A significant improvement of systematic uncertainties motivated the reanalysis of data in pp and Pb-Pb collisions at $\sqrt{s}$$_{NN}$ = 2.76 TeV, as well as in p-Pb collisions at $\sqrt{s}$$_{NN}$ = 5.02 TeV, which is also presented. Spectra from Pb-Pb collisions are presented in nine centrality intervals and are compared to a reference spectrum from pp collisions scaled by the number of binary nucleon-nucleon collisions. For central collisions, the $p_T$ spectra are suppressed by more than a factor of 7 around 6–7 GeV/$c$ with a significant reduction in suppression towards higher momenta up to 30 GeV/$c$. The nuclear modification factor $R_p$Pb, constructed from the pp and p-Pb spectra measured at the same collision energy, is consistent with unity above 8 GeV/$c$. While the spectra in both pp and Pb-Pb collisions are substantially harder at $\sqrt{s}$$_{NN}$ = 5.02 TeV compared to 2.76 TeV, the nuclear modification factors show no significant collision energy dependence. The obtained results should provide further constraints on the parton energy loss calculations to determine the transport properties of the hot and dense QCD matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Energy efficiency in industrial drying: A hybrid ultrasonic system with a novel dynamic optimization framework

Drying processes are among the most energy-consuming operations in industrial and manufacturing settings, demanding strategic selection, design, and control for enhanced efficiency. Advancing drying technologies is critical for improving sustainability, lowering energy use, reducing carbon emissions, and minimizing waste. This study explores two innovative strategies aimed at transforming drying processes into sustainable, low-carbon systems by reducing energy consumption, minimizing waste, and maintaining a strong emphasis on preserving product quality. The first strategy showcases a sub-pilot scale hybrid ultrasonic-convective dryer for agrifood products. This technology, powered by electricity (process electrification), integrates non-thermal ultrasonic dehydration with convective heating and is presented as a sustainable and energy-efficient solution that enhances eco-friendly practices. The second strategy involves introducing and implementing a novel, multiobjective, mixed integer dynamic optimization technique to determine the optimal time-dependent process parameter values for the drying operation. This optimization technique yields operating conditions that are piecewise constant in time aiming to maximize the energy efficiency of the hybrid ultrasonic-convective dryer while ensuring strict adherence to product quality constraints. By adopting the hybrid ultrasonic-convective dryer, a notable 35% improvement in energy efficiency was achieved compared to conventional hot-air drying systems for drying apple slices. The proposed optimization framework further enhanced energy efficiency by nearly 14% over the most efficient process on the identical testbed, under static operating conditions. The reported enhancements have been experimentally validated. Regarding drying time (thereby improving production yield), the developed hybrid ultrasonic-convective dryer demonstrates as much as a 41% reduction in total processing time, which is further optimized by an additional 10% using our proposed optimization framework. The research outcomes have profound implications for the design and operation of drying systems, encompassing crucial aspects such as process electrification, cost-effectiveness, energy savings, time efficiency, product yield, product quality, and process automation.

Dynamic optimization↗
DOE OSTI2018

Theory of activated glassy dynamics in randomly pinned fluids

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Fault geometry inversion and slip distribution of the 2010 M w 7.2 El Mayor-Cucapah earthquake from geodetic data

The 4 April 2010 M w 7.2 El Mayor-Cucapah (EMC) earthquake in Baja, California, and Sonora, Mexico, had primarily right-lateral strike-slip motion and a minor normal-slip component. The surface rupture extended about 120 km in a NW-SE direction, west of the Cerro Prieto fault. We use geodetic measurements including near- to far-field GPS, interferometric synthetic aperture radar (InSAR), and subpixel offset measurements of radar and optical images to characterize the fault slip during the EMC event. We use dislocation inversion methods and determine an optimal nine-segment fault geometry, as well as a subfault slip distribution from the geodetic measurements. With systematic perturbation of the fault dip angles, randomly removing one geodetic data constraint, or different data combinations, we are able to explore the robustness of the inferred slip distribution along fault strike and depth. The model fitting residuals imply contributions of early postseismic deformation to the InSAR measurements as well as lateral heterogeneity in the crustal elastic structure between the Peninsular Ranges and the Salton Trough. We also find that with incorporation of near-field geodetic data and finer fault patch size, the shallow slip deficit is reduced in the EMC event by reductions in the level of smoothing. Finally, these results show that the outcomes of coseismic inversions can vary greatly depending on model parameterization and methodology.

58 GEOSCIENCES↗
DOE OSTI2015

SU-F-BRD-10: Improving Plan Delivery Efficiency of Intensity Modulated Proton Plans with Prioritized Optimization

Purpose: To integrate treatment delivery time into plan optimization in spot scanning intensity modulated proton therapy. Utilizing a dedicated research treatment planning system we present an optimization approach to explore the trade-off between the correlated parameters treatment time and plan quality on an astrocytoma patient case. Methods: The planning system is based on prioritized optimization, a stepwise approach of implementing clinical goals. After each optimization step, dosimetric achievements are turned into hard constraints to maintain the achieved plan quality. Prior achievements can be violated by a so-called slip-factor which allows to study possible trade-offs of conflicting goals. Plan quality is obtained in the first two steps, while the third step optimizes delivery efficiency by working on the spot weight distribution via four alternative Methods: elimination of low weighted spots (1), elimination of spots hardly contributing to PTV dose, followed by reoptimization of the resulting smaller optimization problem (2), reduction of spot weights variance within each energy layer (3), and reduction of the overall spot weight sum (4). Treatment times were calculated assuming either constant or variable beam current depending on the lowest spot weight. Results: Delivery efficiency can be improved remarkably without influencing the plan quality. Absolute time savings depend on the utilized method and facility properties. By varying slip-factor and spot reduction limits, a border of worsening quality is detectable for all methods.Deleting low weighted spots by 10% results in a noticeable decrease in minimum target dose. Further reduction results in more heterogeneous dose distributions and insufficient coverage. Option 2 showed constant plan quality for spot reductions of more than 10%. Conclusion: Including treatment time optimization as a final step into prioritized optimization allows for more efficient treatment plans by redistributing the spot patterns without compromising plan quality, which has to remain the main intent of radiotherapy treatment. The authors report grants from German Research Foundation (DFG) during the conduct of the study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
NASA NTRS2006

Constraints from Comets

Crystalline silicates identified in the laboratory examinations of cometary interplanetary dust particles, in Stardust particles, and in the IR spectra of comets and protoplanetary disks typically have high Mg and low Fe contents. In contrast, the amorphous silicates in IDPs and comets are predominantly Fe-rich. Mg-rich crystalline silicates are hypothesized to form by heating of amorphous silicates at temperatures above 1000 K. Annealing does not change the stoichiometry, i.e., the chemistry of the grains. Therefore, annealing is not expected to change an Fe-bearing amorphous silicate into a Mg-rich crystal. We discuss this challenge to the annealing scenario, review the condensation scenarios, and discuss the possibility that Fe reduction, a process thought to contribute in chondrule-formation, is the missing link between Fe-rich amorphous silicates and Mg rich crystalline silicates. We discuss the time scales for these processes in terms of time dependent 2D models of disks (by Gail & collaborators) and in terms of shocks. We mention the Stardust sample return results on Mg-rich crystalline silicates.

Wooden, Diane H.↗