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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Gamma-ray burst detection prospects for next generation ground-based VHE facilities

ABSTRACT Gamma-ray Bursts (GRB) were discovered by satellite-based detectors as powerful sources of transient γ-ray emission. The Fermi satellite detected an increasing number of these events with its dedicated Gamma-ray Burst Monitor (GBM), some of which were associated with high energy photons ($E \gt 10$ GeV), by the Large Area Telescope (LAT). More recently, follow-up observations by Cherenkov telescopes detected very high energy emission ($E \gt 100$ GeV) from GRBs, opening up a new observational window with implications on the interpretation of their central engines and on the propagation of very energetic photons across the Universe. Here, we use the data published in the 2nd Fermi-LAT Gamma Ray Burst Catalogue to characterize the duration, luminosity, redshift, and light curve of the high energy GRB emission. We extrapolate these properties to the very high energy domain, comparing the results with available observations and with the potential of future instruments. We use observed and simulated GRB populations to estimate the chances of detection with wide-field ground-based γ-ray instruments. Our analysis aims to evaluate the opportunities of the Southern Wide-field-of-view Gamma-ray Observatory (SWGO), to be installed in the Southern Hemisphere, to complement CTA. We show that a low-energy observing threshold ($E_{low} \lt 200$ GeV), with good point source sensitivity ($F_{lim} \approx 10^{-11} \,\mathrm{erg\, cm^{-2}\, s^{-1}}$ in $1$ yr), are optimal requirements to work as a GRB trigger facility and to probe the burst spectral properties down to time-scales as short as $10$ s, accessing a time domain that will not be available to Imaging Atmospheric Cherenkov Telescopes instruments.

La Mura, G. (ORCID:000000018553499X)↗
NASA NTRSDate not supplied

Smart Crop Farming Systems for Artemis Exploration Missions

Space crop production systems that mitigate risks of crew poor performance or illness due to inadequate food and nutrition are needed during manned Artemis exploration missions beyond LEO. Prototype farms must be designed for deployment on ISS and tested in manned platforms: Gateway, lunar habitats, and Mars trans-hab spacecraft in preparation for human missions to Mars. Food production must be optimal and safe for human consumption. Thus, plant growth facilities (i.e. Veggie and APH) can be enhanced with imaging systems (including hyperspectral, multispectral, lidar, and fluorescence imaging systems) for nondestructive monitoring of plant health, stress and assessing food safety. Databases of crop responses to stress obtained during ground studies can be used to develop novel artificial intelligence (AI) algorithms for optimizing crop production (i.e. environmental settings during growth) and for detecting crop indices that ensure food safety. Future farming systems should be sustainable and smart. Novel adaptive AI algorithms requiring limited data sets for calibration are needed for reducing crew intervention during plant cultivation except for maintenance and harvesting events. Eventually, AI driven control systems that include autonomous planting, growing, and harvesting as well as periodic sanitization need evaluation for supplementing crew diets with fresh produce during future Mars exploration missions.

O Monje↗
NASA NTRS1978

Duct wall impedance control as an advanced concept for acoustic suppression enhancement

A systems concept procedure is described for the optimization of acoustic duct liner design for both uniform and multisegment types. The concept was implemented by the use of a double reverberant chamber flow duct facility coupled with sophisticated computer control and acoustic analysis systems. The optimization procedure for liner insertion loss was based on the concept of variable liner impedance produced by bias air flow through a multilayer, resonant cavity liner. A multiple microphone technique for in situ wall impedance measurements was used and successfully adapted to produce automated measurements for all liner configurations tested. The complete validation of the systems concept was prevented by the inability to optimize the insertion loss using bias flow induced wall impedance changes. This inability appeared to be a direct function of the presence of a higher order energy carrying modes which were not influenced significantly by the wall impedance changes.

Dean, P. D.↗
DOE OSTI2024

Evaluating Nationwide Supply Chain for Circularity of PET and Olefin Plastics

PET (Polyethylene Terephthalate, #1) and olefin plastics including HDPE (High Density Polyethylene, #2), LDPE/LLDPE (Low Density/Linear Low-Density Polyethylene, #4) and PP (Polypropylene, #5) together comprise nearly 80% of the U.S. plastic market. Due to their high market share and extensive application in packaging these polymers have better potential for circularity than other polymer types. To understand the potential of future scenarios with higher recycling rates, supply chain scenarios for PET and olefin plastic packaging need to be analyzed with increased availability and collection of plastics. Currently there exists a knowledge gap to understand the circular supply chain on a national level. Performing a nationwide analysis introduces certain challenges such as variability in the plastic mix of the recycling stream in different municipalities, lack of collection of some types of plastics, regional differences in cost and estimating a national supply curve based on state level access rate and participation rate. Currently, a limited number of Plastic Reclaimers recycle the nation’s collected plastic involving transportation over long distances surpassing state boundaries. Modeling a nationwide scenario instead of regional/state based scenario will facilitate transportation beyond state boundaries for the development of a circular economy. A Mixed-integer Linear Programming model was developed, to identify the optimal location and capacity of the Material Recovery Facilities (MRFs) nationwide subject to maximizing the profit margin of the industrial entities within the model. We considered three different scenarios including the base case scenario (S1) collecting 2.27 million metric tons/year as well as two additional scenarios with available plastic supply of 1.8 times (S2) and 2.2 times (S3) of the base case scenario. The model identified 166, 275 and 319 counties as potential MRF locations for scenarios S1, S2 and S3 respectively. Compared to the existing number of counties having MRFs in the US, the model results indicated a reduction of 38% of MRFs for S1. For S2 and S3, the number of counties with MRFs increased 3% and 20% respectively compared to counties currently with MRFs. The average profit remains constant between $180-$181/ton regardless of the increased plastic collection.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗
DOE OSTI2025

On measuring stimulated photon–photon scattering using multiple ultraintense lasers

Stimulated photon–photon scattering is a predicted consequence of quantum electrodynamics that has yet to be measured directly. Measuring the cross section for stimulated photon–photon scattering is the aim of a flagship experiment for NSF OPAL, a proposed laser user facility with two, 25-PW beamlines. We present optimized experimental designs for achieving this challenging and canonical measurement. A family of experimental geometries is identified that satisfies the momentum- and energy-matching conditions for two selected laser frequency options. Numerical models predict a maximum signal exceeding 1000 scattered photons per shot at the experimental conditions envisaged at NSF OPAL. Experimental requirements on collision geometry, polarization, cotiming and copointing, background suppression, and diagnostic technologies are investigated numerically. These results confirm that a beam cotiming shorter than the pulse duration and control of the copointing on a scale smaller than the shortest laser wavelength are needed to robustly scatter photons on a per-shot basis. Finally, we assess the bounds that a successful execution of this experiment may place on the mass scale of Born–Infeld nonlinear electrodynamics beyond the standard model of physics.

Beyond the Standard Model↗
DOE OSTI2022

Performance Analysis and Optimization for Scientific Data Workloads

Scientific data generated at experimental and observational facilities are increasingly being processed on large-scale compute systems. Most of the experimental data analysis workflows are not designed or implemented to run on large scale environments and take full advantage of HPC compute and storage resources. These applications are unlike the traditional tightly-coupled scientific applications and hence face significant performance and scalability challenges as the volume of data increases exponentially. In this paper, we conduct a performance and scalability analysis for experimental analysis applications and workflows operating on data from light sources. Our analysis detects and quantifies I/O performance, scalability and runtime bottlenecks for three data analysis applications that run on NERSC resources. Based on our analysis we propose and implement a set of optimizations that lead to reducing the amount of time spent on I/O operations by almost 90%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Disjunctive optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems

This paper proposes a new optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems. The model optimizes both investment decisions (e.g., size, location, and time to install, retire and decommission facilities) and operation decisions (e.g., on/off status, operating capacity, and expected power output). It is also able to optimize reserve systems (or backup systems), as well as the main systems, to improve power systems reliability. An impact of operational strategies of generators (i.e., participating in electricity production vs. remaining as idle units during operation) on power systems reliability is considered. Probability of equipment failures and capacity failure states are used to rigorously estimate the power systems reliability depending on design and operation strategies. The optimization model is formulated with Generalized Disjunctive Programming (GDP), which is reformulated as a mixed-integer linear programming (MILP) model using the Hull relaxation. Two reliability-related penalties, such as downtime penalty and unmet demand penalty, are included in the objective function to maximize reliability while minimizing the total net present cost. Furthermore, a bilevel decomposition with tailored cuts is developed to reduce computational times of the multi-scale optimization model. The effectiveness of the proposed model is shown by comparing the results with the results obtained from the expansion planning models that do not explicitly consider reliability. In conclusion, we also show that the proposed bilevel decomposition is computationally efficient for solving large scale problems through 5-years and 10-years planning case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Simulating Magnetized Electron Cooling for EIC with JSPEC

We present a possible electron cooling configuration for the proposed Electron Ion Collider (EIC) facility, developed using a Nelder-Mead Simplex optimization procedure built into JSPEC, an electron cooling code developed at Jefferson Lab. We show the time evolution of the emittance of the ion beam in the presence of this cooler evaluated assuming the ion distribution remains Gaussian. We also show that bi-gaussian distributions emerge in simulations of ion macro-particles. We show how intra-beam scattering can be treated with a core-tail model in simulations of ion macro-particles. The Sirepo/JSPEC* and Sirepo/Jupyter** apps will be presented, with instructions enabling the community to reproduce our simulations.

Coleman, S. J.↗
DOE OSTI2020

Domestic Hot Water Temperature Maintenance Technology Review

Domestic hot water temperature maintenance (HWTM) is an important topic in facility management, and there are often opportunities to optimize systems to achieve energy, water, and maintenance savings. The main purpose of an HWTM system is to provide reliable hot water temperature at all fixtures with minimal wait time. This is done by replacing the standby heat losses from hot water sitting idle in pipes during periods of low demand. Traditionally, most commercial buildings do this by having water recirculate back to the water heater to be reheated. Other currently available HWTM systems are also discussed in this resource. HWTM systems can help maintain water at appropriate temperatures, minimize heat loss, and minimize delivery times to fixtures to improve the function of a building. This webpage includes a summary of HWTM options along with important considerations regarding occupant safety and comfort, and maintenance strategies for optimal and efficient operations. Domestic hot water (DHW) generation systems are referred to but are not the focus of this resource.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Small Modular Reactor and Microreactor Security-by-Design Lessons Learned: Integrated PPS Designs

U.S. nuclear power facilities face increasing challenges in meeting dynamic security requirements caused by evolving and expanding threats while keeping costs reasonable to make nuclear energy competitive. The past approach has often included implementing security features after a facility has been designed and without attention to optimization, which can lead to cost overruns. Incorporating security into the design process can provide robust, cost-effective, and sufficient physical protection systems. The purpose of this report is to capture lessons learned by the Advanced Reactor Safeguards and Security (ARSS) program that may be beneficial for other advanced and small modular reactor (SMR) vendors to use when developing security systems and postures. This report will capture relevant information that can be used in the security-by-design (SeBD) process for SMR and microreactor vendors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1989

Hybrid Propulsion Technology Program, phase 1. Volume 1: Executive summary

The study program was contracted to evaluate concepts of hybrid propulsion, select the most optimum, and prepare a conceptual design package. Further, this study required preparation of a technology definition package to identify hybrid propulsion enabling technologies and planning to acquire that technology in Phase 2 and demonstrate that technology in Phase 3. Researchers evaluated two design philosophies for Hybrid Rocket Booster (HRB) selection. The first is an ASRM modified hybrid wherein as many components/designs as possible were used from the present Advanced Solid Rocket Motor (ASRM) design. The second was an entirely new hybrid optimized booster using ASRM criteria as a point of departure, i.e., diameter, thrust time curve, launch facilities, and external tank attach points. Researchers selected the new design based on the logic of optimizing a hybrid booster to provide NASA with a next generation vehicle in lieu of an interim advancement over the ASRM. The enabling technologies for hybrid propulsion are applicable to either and vehicle design may be selected at a downstream point (Phase 3) at NASA's discretion. The completion of these studies resulted in ranking the various concepts of boosters from the RSRM to a turbopump fed (TF) hybrid. The scoring resulting from the Figure of Merit (FOM) scoring system clearly shows a natural growth path where the turbopump fed solid liquid staged combustion hybrid provides maximized payload and the highest safety, reliability, and low life cycle costing.

Source record↗
NASA NTRS1995

Internal aerodynamics of a generic three-dimensional scramjet inlet at Mach 10

A combined computational and experimental parametric study of the internal aerodynamics of a generic three-dimensional sidewall compression scramjet inlet configuration at Mach 10 has been performed. The study was designed to demonstrate the utility of computational fluid dynamics as a design tool in hypersonic inlet flow fields, to provide a detailed account of the nature and structure of the internal flow interactions, and to provide a comprehensive surface property and flow field database to determine the effects of contraction ratio, cowl position, and Reynolds number on the performance of a hypersonic scramjet inlet configuration. The work proceeded in several phases: the initial inviscid assessment of the internal shock structure, the preliminary computational parametric study, the coupling of the optimized configuration with the physical limitations of the facility, the wind tunnel blockage assessment, and the computational and experimental parametric study of the final configuration. Good agreement between computation and experimentation was observed in the magnitude and location of the interactions, particularly for weakly interacting flow fields. Large-scale forward separations resulted when the interaction strength was increased by increasing the contraction ratio or decreasing the Reynolds number.

Holland, Scott D.↗
DOE OSTI2020

EVALUATING FACILITY ENERGY EFFICIENCY AND RESILIENCE OPPORTUNITIES WITH FEDS AND MCOR

Energy resilience has become increasingly important for critical building infrastructure, in response to concerns over potential disruptions to the electrical grid from threats both natural and man-made. Energy efficiency can provide a valuable resource for reducing critical loads and therefore lowering the cost of supplying alternative power. This paper highlights two tools that are well-suited for analyzing building energy efficiency and resilience opportunities and presents a case study for their combined application. The Facility Energy Decision System (FEDS) and Microgrid Component Optimization for Resilience (MCOR) tools can be used together to simulate building systems, identify energy efficiency measures, and evaluate resilience options for powering a site during an outage.

FEDS, MCOR, Energy Efficiency, Resilience, Simulat↗
DOE OSTI2026

Explainable physics-based constraints on reinforcement learning for accelerator optimization

We present a reinforcement learning (RL) framework for optimizing particle accelerator experiments that builds explainable physics-based constraints on agent behavior. The goal is to increase transparency and trust by letting users verify that the agent’s decision-making process incorporates suitable physics. Our algorithm uses a learnable surrogate function for physical observables, such as energy, and uses them to fine-tune how actions are chosen. This surrogate can be represented by a neural network or by an interpretable sparse dictionary model. We test our algorithm on a range of particle accelerator optimization environments designed to emulate the Continuous Electron Beam Accelerator Facility at Jefferson Lab. By examining the mathematical form of the learned constraint function, we are able to confirm the agent has learned to use the established physics of each environment. In addition, we find that the introduction of a physics-based surrogate enables our RL algorithms to reliably converge for difficult high-dimensional accelerator optimization environments.

explainability↗
NASA NTRS1997

Facilitating Science--The International Space Station Fluids and Combustion Facility

Scientists in many fields would like to perform experiments on the International Space Station (ISS) to take advantage of the unique environment of microgravity (which is the near-absence of gravity). The ISS will provide the opportunity for scientists to perform microgravity tests over much longer time periods than previously available on the space shuttle--months rather than hours or days--providing more data that could lead to new discoveries. Many of the experiments on ISS will be conducted through the use of new microgravity science facilities. A microgravity science facility is a complete system of on-orbit and ground (on-Earth) hardware, software, operations, and plans that have been optimized to perform sustained microgravity research in one or two scientific disciplines. The facility concept includes hardware that remains on-orbit (because of its general usefulness) and a small amount of unique hardware that is developed for each principal investigator. Such unique hardware customizes the facility to perform a given principal investigator's experiment effectively. Many facilities are planned for the ISS to accommodate scientists' needs. While the quality and quantity of scientific data are being improved, per-experiment costs will be lowered relative to other ways of performing such experiments. The NASA Lewis Research Center is developing a Fluids and Combustion Facility (FCF) to perform microgravity fluids and combustion experiments on the ISS. The FCF will be the lowest cost, most resource efficient approach to performing fluid physics and combustion science experiments on the ISS. Experiments performed in the FCF will be 3 to 9 times less expensive than similar Spacelab experiments. Moreover, use of key ISS resources, such as upmass, power, cooling, and astronaut crew time, will be cut by the same factor.

Winsa, Edward A.↗
DOE OSTI2025

Xopt and Badger: a machine learning ecosystem for real-time accelerator control and optimization

Machine learning (ML)-based black-box optimization algorithms have demonstrated significant improvements in accelerator optimization speed, often by orders of magnitude. However, deploying these algorithms in real-time facility control remains challenging due to the specialized expertise and infrastructure required. To bridge this gap, we introduce the Xopt ecosystem, a versatile suite of tools designed to make advanced ML-based optimization accessible to the broader accelerator community. This ecosystem includes Xopt, a modular Python framework that facilitates the integration of ML-based optimization algorithms with arbitrary control problems, and Badger, a graphical user interface built on top of Xopt, which enables seamless deployment of ML algorithms in real-time control systems. The Xopt ecosystem has been successfully applied towards solving challenging real-time control problems at leading international accelerator facilities, including SLAC, LBNL, Argonne, Fermilab, BNL, DESY, and ESRF, demonstrating its effectiveness in real-world optimization tasks. In this presentation, we provide an overview of Xopt’s capabilities and illustrate its impact through case studies from SLAC accelerator facilities including LCLS, LCLS-II, and FACET-II.

Roussel, Ryan [SLAC]↗
DOE OSTI2023

Scaling for Nuclear Reactor System: Overview

A scaling analysis is essential for predicting the behavior of a reactor system under various operating conditions, as well as for ensuring safe and reliable experimentation and adequate dataset generation for supporting the system code model development and assessment in accordance with USNRC guidelines 1.203. Testing and modeling can be carried out at various scales, from small test units to full-scale reactors, to validate the predictions produced by the analysis. However, due to the cost and challenges associated with full-scale testing, the nuclear industry uses scaled test facilities—integral effect test (IET) and separate effect test (SET)—to identify potential design issues and optimize the design to ensure regulatory compliance for safer operation and anticipated accident management. In general, IET facilities are non-nuclear thermal hydraulics test facilities. In contrast, SET facilities can be non-nuclear testing (e.g., steam generator, containment, pump system SETs) and nuclear testing (mostly fuel-material irradiation testing). IETs are used to study the system-level thermal-hydraulic behavior of the reactor coolant system (RCS) under different anticipated operational occurrences (AOOs) and design basis accidents (DBAs) such as loss-of-coolant-accident (LOCA) and loss-of-power (i.e., station blackout) and loss-of-flow (i.e., failure of RCS pump). Several LOCA scenarios could happen in reactor DBAs, such as main steam line break (MSLB), SG tube rapture (SGTR), break in direct vessel injection (DVI), and other small breaks LOCA. Scaling analysis determines the appropriate size and operating conditions for the test facility. This involves analyzing the system's thermal-hydraulic behavior at different scales and identifying the key parameters that affect the thermal-hydraulic behavior of the reactor. These key parameters can be identified so that the scaled facility can replicate the expected conditions in a prototypical setting. The scaled facility can simulate the same flow rates, pressure gradients, heat transfer coefficients, and fluid properties as the prototype. Scaling analysis is used to ensure that the results from these tests can be scaled up to predict the behavior of a full-scale prototype with an acceptable range of scaling distortions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗