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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 181 records · Page 10

Acceleration of Power System Dynamic Simulations Using a Deep Equilibrium Layer and Neural ODE Surrogate

The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along with the rapid integration of inverter-based resources exacerbates the computational burden of running time domain simulations. Here, in this paper, we propose a data-driven surrogate model based on implicit machine learningspecifically deep equilibrium layers and neural ordinary differential equationsto learn a reduced order model of a portion of the full underlying system. The data-driven surrogate achieves similar accuracy and reduction in simulation time compared to a physics-based surrogate, without the constraint of requiring detailed knowledge of the underlying dynamic models. This work also establishes key requirements needed to integrate the surrogate into existing simulation workflows; the proposed surrogate is initialized to a steady state operating point that matches the power flow solution by design.

Neural ordinary differential equations↗

An improved linear ion trap physics package

This article describes an improvement in the architecture of the physics package used in the Linear Ion Trap (LIT)-based frequency standard recently developed at JPL. This new design is based on the observation that ions can be moved along the axis of an LIT by applied dc voltages. The state selection and interrogation region can be separated from the more critical microwave resonance region where the multiplied local oscillator signal is compared with the stable atomic transition. This separation relaxes many of the design constraints of the present units. Improvements include increased frequency stability and a substantial reduction in size, mass, and cost of the final frequency standard.

Prestage, J. D.↗

Use of Rig Parameter Data in Bit Constraint Models for Improved Drilling Performance at The Geysers

Surface parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. However, these measurements are of reduced value without a standard to aid in evaluation and decision making. A method is demonstrated whereby drill bit constraint models are used to interpret drilling response parameters. Drill rig parameter data for well GDC-36 at the Geysers Geothermal Field Power were acquired by Geysers Power Company and drilling contractor Kenai Drilling using Pason US DataHub and evaluated. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) along with other model constraints in computational algorithms. The method is used to evaluate overall bit performance, monitor bit integrity, and detect the presence of drillstring vibrations and other conditions contributing to bit failure; comparisons are made to observations of bit wear and damage. The method will be applied in real-time to improve decision-making on subsequent wells and has applicability to development of advanced analytics on future geothermal wells using real-time electronic drilling recorder (EDR) data for improved performance and reduced drilling costs.

15 GEOTHERMAL ENERGY↗

Mass Reduction: The Weighty Challenge for Exploration Space Flight

Meeting nutritional and acceptability requirements is critical for the food system for an exploration class space mission. However, this must be achieved within the constraints of available resources such as water, crew time, stowage volume, launch mass and power availability.  Due to resource constraints, exploration class missions are not expected to have refrigerators or freezers for food storage, and current per person food mass must be reduced to improve mission feasibility.  The Packaged Food Mass Reduction Trade Study (Stoklosa, 2009) concluded that the mass of the current space food system can be effectively reduced by decreasing water content of certain foods and offering nutrient dense substitutes, such as meal replacement bars and beverages. Target nutrient ranges were established based on the nutritional content of the current breakfast and lunch meals in the ISS standard menu. A market survey of available commercial products produced no viable options for meal replacement bar or beverage products. New prototypes for both categories were formulated to meet target nutrient ranges. Samples of prototype products were packaged in high barrier packaging currently used for ISS and underwent an accelerated shelf life study at 31 degC and 41 degC (50% RH) for 24 weeks. Samples were assessed at the following time points: Initial, 6 weeks, 12 weeks, and 24 weeks. Testing at each time point included the following: color, texture, water activity, acceptability, and hexanal analysis (for food bars only). Proof of concept prototypes demonstrated that meal replacement food bars and beverages can deliver a comparable macronutrient profile while reducing the overall mass when compared to the ISS Standard Menu. Future work suggestions for meal replacement bars: Reformulation to include ingredients that reduce hardness and reduce browning to increase shelf life. Micronutrient analysis and potential fortification. Sensory evaluation studies including satiety tests and menu fatigue. Water Intake Analysis: The water in thermostabilized foods is considered as part of a crewmember's daily water intake. Extensive meal replacement would require further analyses to determine if additional water provisioning would be required per crewmember negating some of the mass savings.

Kloeris, Vickie L.↗

RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design

Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural constraints. This work presents RLMolLM, a reinforcement learning framework combining Proximal Policy Optimization (PPO) with genetic algorithms to address these limitations. Our approach optimizes multiple user-specified properties including quantitative estimates of drug-likeness (QED), synthetic accessibility (SA), and ADMET (absorption, distribution, metabolism, excretion, and toxicity) endpoints without requiring complete model retraining, while maintaining capability for scaffold-constrained generation where specific substructures must be preserved. We outperform state-of-the-art methods for molecular optimization, achieving best QED scores across GDB13, Moses, and Zinc datasets with up to 31% improvement over previous methods while maintaining excellent validity, uniqueness, and novelty metrics. For simultaneous multi-property optimization, our framework achieves substantial improvements in ADMET properties including 4.5-fold reduction in hERG toxicity and enhanced Caco-2 permeability compared to Moses dataset. Under structural constraints, the framework significantly improves molecular validity while preserving scaffolds and effectively optimizing properties. In conclusion, this versatile solution advances pharmaceutical and materials molecular design through effective integration of reinforcement learning and genetic algorithms with multi-property optimization and scaffold preservation.

Genetic algorithms↗

Analysis of Separation Corridors for Visiting Vehicles from the International Space Station

The International Space Station (ISS) is a very dynamic vehicle with many operational constraints that affect its performance, operations, and vehicle lifetime. Most constraints are designed to alleviate various safety concerns that are a result of dynamic activities between the ISS and various Visiting Vehicles (VVs). One such constraint that has been in place for Russian Vehicle (RV) operations is the limitation placed on Solar Array (SA) positioning in order to prevent collisions during separation and subsequent relative motion of VVs. An unintended consequence of the SA constraint has been the impacts to the operational flexibility of the ISS resulting from the reduced power generation capability as well as from a reduction in the operational lifetime of various SA components. The purpose of this paper is to discuss the technique and the analysis that were applied in order to relax the SA constraints for RV undockings, thereby improving both the ISS operational flexibility and extending its lifetime for many years to come. This analysis focused on the effects of the dynamic motion that occur both prior to and following RV separations. The analysis involved a parametric approach in the conservative application of various initial conditions and assumptions. These included the use of the worst case minimum and maximum vehicle configurations, worst case initial attitudes and attitude rates, and the worst case docking port separation dynamics. Separations were calculated for multiple ISS docking ports, at varied deviations from the nominal undocking attitudes and included the use of two separate attitude control schemes: continuous free-drift and a post separation attitude hold. The analysis required numerical propagation of both the separation motion and the vehicle attitudes using 3-degree-of-freedom (DOF) relative motion equations coupled with rigid body rotational dynamics to generate a large set of separation trajectories.

Zaczek, Mariusz P.↗

Conformal Avoidance of Normal Organs at Risk by Perfusion-Modulated Dose Sculpting in Tumor Single-Dose Radiation Therapy

Although 24 Gy single-dose radiation therapy (SDRT) renders >90% 5-year local relapse-free survival in human solid tumor lesions, SDRT delivery is not feasible in ∼50% of oligometastatic lesions owing to interference by dose/volume constraints of a serial organ at risk (OAR). Conformal OAR avoidance is based on a hypothetical model positing that the recently described SDRT biology specifically permits volumetric subdivision of the SDRT dose, such that high-intensity vascular drivers of SDRT lethality, generated within a major tumor subvolume exposed to a high 24 Gy dose (high-dose planning target volume [PTV{sub HD]}), would equilibrate SDRT signaling intensity throughout the tumor interstitial space, rendering bystander radiosensitization of a minor subvolume (perfusion-modulated dose sculpting PTV [PTV{sub PMDS}]), dose-sculpted to meet a serial OAR dose/volume constraint. An engineered PTV{sub PMDS} may thus yield tumor ablation despite PMDS dose reduction and conformally avoiding OAR exposure to a toxic dose.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Indirect measurement of the 90 Sr ⁢(𝑛, 𝛾)⁢ 91 Sr reaction cross section and the implications for astrophysical Zr production

Here, the intermediate neutron-capture process (𝑖 process) has gained notable traction within the past decade as a way to describe stellar abundance observations which cannot be explained by the slow and rapid neutron-capture processes. Despite the general success of 𝑖-process models, many open questions remain. Among the observations, Zr stands out, as its elemental abundance is difficult to replicate with available 𝑖-process models, while the reactions that affect its production through the 𝑖 process are close enough to stability to study experimentally. Here, we present the experimental constraint of the nuclear level density and 𝛾-strength function (𝛾 SF) of 91 Sr using the 𝛽-Oslo method, which were then input into the TALYS Hauser-Feshbach code to produce the first experimental constraint of the 90 Sr ⁢(𝑛, 𝛾)⁢ 91 Sr capture reaction. This constraint was used alongside that of 92 Sr ⁢(𝑛, 𝛾)⁢ 93 Sr for a reduction in the uncertainty of [Y/Zr] production in the 𝑖-process relevant environmental neutron density of 10 13.5 and 10 14.5 neutrons/cm 3 .

Physics - Nuclear physics and radiation physics↗

New Data-Driven Constraints on the Sign of Gluon Polarization in the Proton

Recently, the possible existence of negative gluon helicity Δ g has been observed to be compatible with existing empirical constraints, including from jet production in polarized proton-proton collisions at the Relativistic Heavy Ion Collider, and lattice QCD data on polarized gluon Ioffe time distributions. We perform a new global analysis of polarized parton distributions in the proton with new constraints from the high- x region of deep-inelastic scattering (DIS). A dramatic reduction in the quality of the fit for the negative Δ g replicas compared to those with positive Δ g suggests that the negative Δ g solution cannot simultaneously account for high- x polarized DIS data along with lattice and polarized jet data. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimal recovery from microburst wind shear

The flight path of a twin-jet transport aircraft is optimized in a microburst encounter during approach to landing. The objective is to execute an escape maneuver that maintains safe ground clearance and an adequate stall margin during the climb-out portion of the trajectory. A cost function penalizing rate of climb deviations from a nominal value and rate of elevator deflection produces qualitatively good results in a variety of microburst encounters. The optimal maneuver is a gradual pitch-up that ceases near the core of the microburst, followed by a slight reduction in pitch attitude in the tailwind area of the microburst. A minimum airspeed constraint in the optimization prevents excessive airspeed loss in very severe microbursts. The aircraft equations of motion include short-period dynamics, so that the optimization solves directly for the control surface deflections required to achieve the optimal flight paths.

Mulgund, Sandeep S.↗

Reduction method with system analysis for multiobjective optimization-based design

An approach for reducing the number of variables and constraints, which is combined with System Analysis Equations (SAE), for multiobjective optimization-based design is presented. In order to develop a simplified analysis model, the SAE is computed outside an optimization loop and then approximated for use by an operator. Two examples are presented to demonstrate the approach.

Azarm, S.↗

Gradient-based constrained optimization using a database of linear reduced-order models

A methodology grounded in model reduction is presented for accelerating the gradient-based solution of a family of linear or nonlinear constrained optimization problems where the constraints include at least one linear Partial Differential Equation (PDE). A key component of this methodology is the construction, during an offline phase, of a database of pointwise, linear, Projection-based Reduced-Order Models (PROM)s associated with a design parameter space and the linear PDE(s). A parameter sampling procedure based on an appropriate saturation assumption is proposed to maximize the efficiency of such a database of PROMs. A real-time method is also presented for interpolating at any queried but unsampled parameter vector in the design parameter space the relevant sensitivities of a PROM. The practical feasibility, computational advantages, and performance of the proposed methodology are demonstrated for several realistic, nonlinear, aerodynamic shape optimization problems governed by linear aeroelastic constraints.

97 MATHEMATICS AND COMPUTING↗

A demonstration of improved constraints on primordial gravitational waves with delensing

We present a constraint on the tensor-to-scalar ratio, $r$, derived from measurements of cosmic microwave background (CMB) polarization $B$-modes with "delensing,'' whereby the uncertainty on $r$ contributed by the sample variance of the gravitational lensing $B$-modes is reduced by cross-correlating against a lensing $B$-mode template. This template is constructed by combining an estimate of the polarized CMB with a tracer of the projected large-scale structure. The large-scale-structure tracer used is a map of the cosmic infrared background derived from Planck satellite data, while the polarized CMB map comes from a combination of South Pole Telescope, BICEP/Keck, and Planck data. We expand the BICEP/Keck likelihood analysis framework to accept a lensing template and apply it to the BICEP/Keck data set collected through 2014 using the same parametric foreground modelling as in the previous analysis. From simulations, we find that the uncertainty on $r$ is reduced by $\sim10\%$, from $\sigma(r)$= 0.024 to 0.022, which can be compared with a $\sim26\%$ reduction obtained when using a perfect lensing template. Applying the technique to the real data, the constraint on $r$ is improved from $r_{0.05} < 0.090$ to $r_{0.05} < 0.082$ (95% C.L.). Furthermore, this is the first demonstration of improvement in an $r$ constraint through delensing.

79 ASTRONOMY AND ASTROPHYSICS↗

Unified nonparametric equation-of-state inference from the neutron-star crust to perturbative-QCD densities

Perturbative quantum chromodynamics (pQCD), while valid only at densities exceeding those found in the cores of neutron stars, could provide constraints on the dense-matter equation of state (EOS). Here, in this work, we examine the impact of pQCD information on the inference of the EOS using a nonparametric framework based on Gaussian processes (GPs). We examine the application of pQCD constraints through a ``pQCD likelihood,'' and verify the findings of previous works; namely, a softening of the EOS at the central densities of the most massive neutron stars and a reduction in the maximum neutron-star mass. Although the pQCD likelihood can be easily integrated into existing EOS inference frameworks, this approach requires an arbitrary selection of the density at which the constraints are applied. The EOS behavior is also treated differently on either side of the chosen density. To mitigate these issues, we extend the EOS model to higher densities, thereby constructing a ``unified'' description of the EOS from the neutron-star crust to densities relevant for pQCD. In this approach the pQCD constraints effectively become part of the prior. Since the EOS is unconstrained by any calculation or data between the densities applicable to neutron stars and pQCD, we argue for maximum modeling flexibility in that regime. We compare the unified EOS with the traditional pQCD likelihood, and although we confirm the EOS softening, we do not see a reduction in the maximum neutron-star mass or any impact on macroscopic observables. Though residual model dependence cannot be ruled out, we find that pQCD suggests the speed of sound in the densest neutron-star cores has already started decreasing toward the asymptotic limit; we find that the speed of sound squared at the center of the most massive neutron star has an upper bound of $\sim 0.5$ at the 90% level.

equations of state of nuclear matter↗

Efficient sensitivity analysis and optimization of a helicopter rotor

Aeroelastic optimization of a system essentially consists of the determination of the optimum values of design variables which minimize the objective function and satisfy certain aeroelastic and geometric constraints. The process of aeroelastic optimization analysis is illustrated. To carry out aeroelastic optimization effectively, one needs a reliable analysis procedure to determine steady response and stability of a rotor system in forward flight. The rotor dynamic analysis used in the present study developed inhouse at the University of Maryland is based on finite elements in space and time. The analysis consists of two major phases: vehicle trim and rotor steady response (coupled trim analysis), and aeroelastic stability of the blade. For a reduction of helicopter vibration, the optimization process requires the sensitivity derivatives of the objective function and aeroelastic stability constraints. For this, the derivatives of steady response, hub loads and blade stability roots are calculated using a direct analytical approach. An automated optimization procedure is developed by coupling the rotor dynamic analysis, design sensitivity analysis and constrained optimization code CONMIN.

Lim, Joon W.↗

Equitable Urban Electric Vehicle Charging: Feasibility and Benefits of Streetlight Charging in Kansas City Right-of-Way

With an increasing global emphasis on sustainability, electric vehicles (EVs) play a crucial role in reducing urban pollution and carbon emissions. For EVs to be widely adopted, equitable and convenient access to charging infrastructure is essential. Equity in this paper refers to the proactive engagement with the community to ensure that the benefits of streetlight charging are distributed equitably across diverse neighborhoods in Kansas City, providing fair charging opportunities and resources to all community members. This research explores the potential of utilizing streetlights—ubiquitous elements of urban electrical infrastructure—as low-cost, equitable EV charging solutions. Compared with conventional chargers, streetlight charging offers several notable advantages, including proximity to roadways, potential boosts to the local economy, and easier usage due to city ownership. These chargers also leverage existing power setups to minimize costs and maximize efficiency by reutilizing existing structures. In this manuscript, we introduce a systematic framework to develop, analyze, and evaluate a scalable and cost-effective streetlight charging solution. Initially, we employ a two-tiered site selection framework that accounts for both charging demand and equity considerations to identify optimal locations for streetlight chargers. We then assess the feasibility of these chargers through observational data from 23 units installed in Kansas City, Missouri, comparing their performance with traditional chargers. Here, our evaluation extends to the environmental impact, comparing reduced gasoline consumption and greenhouse gas (GHG) emission reductions between streetlights and regular charging stations. Our findings reveal that streetlight charging stations offer faster charging speeds than conventional stations, validating their viability for EV charging. Additionally, the duration of stay at streetlight chargers tends to be shorter, likely due to parking constraints or associated costs. Furthermore, streetlight-powered chargers demonstrate considerable environmental advantages, achieving 11.94% greater avoided gasoline consumption and 11.24% higher GHG reductions compared with regular charging stations, highlighting their substantial environmental benefits.

42 ENGINEERING↗

Online Modelling and Optimization of Nonlinear Integrable Systems

Nonlinear integrable optics was recently proposed as a design approach to increase the limits on beam brightness and intensity imposed by fast collective instabilities. To study these systems experimentally, a new research electron and proton storage ring, the Integrable Optics Test Accelerator, was constructed and recently commissioned at Fermilab. Beam-based diagnostics and online modelling of nonlinear systems presents unique challenges - in this paper, we report on our efforts to develop optimization methods suited for such lattices. We explore the effectiveness of neural networks as fast online surrogate estimators, and integrate them into a beam-based tuning algorithm. We also develop a method of knob dimensionality reduction and subsequent robust multivariate optimization for maximizing key performance metrics under complicated lattice optics constraints.

43 PARTICLE ACCELERATORS↗