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Results for “constraint energy minimization”

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 235 records · Page 13

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NASA NTRS1983

Orbital transfer and release of tethered payloads. Continuation of investigation of electrodynamic stabilization and control of long orbiting tethers Martinez-Sanchez, Manuel

The effect of reeling operations on the orbital altitude of the tether system and the development of control laws to minimize tether rebound upon payload release were studied. The use of the tether for LEO/GEO payload orbital transfer was also investigated. It was concluded that (1) reeling operations can contribute a significant amount of energy to the orbit of the system and should be considered in orbit calculations and predictions, (2) deployment of payloads, even very large payloads, using tethers is a practical and fully stable operation, (3) tether augmented LEO/GEO transfer operations yield useful payload gains under the practical constraint of fixed size OTV's, and (4) orbit to orbit satellite retrieval is limited by useful revisit times to orbital inclinations of less than forty-five degrees.

Colombo, G.↗

DOE OSTI2020

A metric framework for evaluating the resilience contribution of hydropower to the grid

This paper will describe a proposed framework for expressing the resilience of hydropower generation and provide initial case studies for three classes of hydropower, run-of-river hydropower, hydropower with reservoirs, and pumped storage hydropower. Hydropower has great flexibility to provide support during and after natural and man-made events that can disrupt critical infrastructure functionality. The concept of the framework provides for consideration of policy and rules, constraints of the water shed and other allocations of water, storage and plant capabilities to produce real and reactive power, and the strength of the delivery network. The paper details a resilience response metric that has inputs of state of storage and plant level constraints on real and reactive power production. Using the definition of resilience, based on maintaining a minimally normal operations, we provide a qualitative assessment of hydropower’s ability to address the various time scales comprising the “R”s of resilience.

13 HYDRO ENERGY↗

DOE OSTI2026

Algebraic Multigrid with Filtering: An Efficient Preconditioner for Interior Point Methods in Large-Scale Contact Mechanics Optimization

Large-scale contact mechanics simulations are crucial in many engineering fields such as structural design and manufacturing. In the frictionless case, contact can be modeled by minimizing an energy functional; however, these problems are often nonlinear, nonconvex, and increasingly difficult to solve as mesh resolution increases. In this work, we employ a Newton-based interior-point (IP) filter line-search method, an effective approach for large-scale constrained optimization. While this method converges rapidly, each iteration requires solving a large saddle-point linear system that becomes ill-conditioned as the optimization process converges, largely due to IP treatment of the contact constraints. Such ill-conditioning can hinder solver scalability and increase iteration counts with mesh refinement. Here, to address this, we introduce a novel preconditioner, algebraic multigrid with filtering (AMGF), tailored to the Schur complement of the saddle-point system. Building on the classical AMG solver, commonly used for elasticity, we augment it with a specialized subspace correction that filters near null space components introduced by contact interface constraints. Through theoretical analysis and numerical experiments on a range of linear and nonlinear contact problems, we demonstrate that the proposed solver achieves mesh independent convergence and maintains robustness against the ill-conditioning that notoriously plagues IP methods. These results indicate that AMGF makes contact mechanics simulations more tractable and broadens the applicability of Newton-based IP methods in challenging engineering scenarios. More broadly, AMGF is well suited for problems, optimization or otherwise, where solver performance is limited by a low-dimensional subspace, such as those arising from localized constraints, interface conditions, or model heterogeneities. This makes the method widely applicable beyond contact mechanics and constrained optimization.

Mathematics and Computing↗

DOE OSTI2026

Big Data Meets Geothermal Exploration (CRADA Final Report)

As part of the Cyclotron Road program, Zanskar Geothermal & Minerals, Inc. investigated the application of micro-earthquake and ambient noise seismology methods to imaging and characterizing the structural characteristics and hydrothermal flux of subsurface faults. Significant advances in what could be resolved were enabled by two major developments in seismology: 1) the availability of large-n arrays of low-cost seismometers, and 2) the availability of increased computational power and semi-automated data reduction algorithms. In tandem, these advances may improve the signal-to-noise ratio and spatial precision of the data collected and enable higher-resolution characterization of subsurface fracture systems and their spatio-temporal evolution. These tools supported efforts to reduce dry-hole risk and to improve wellfield productivity for geothermal resource development. In particular, two applications of these advances were evaluated: 1) fracture-seismic imaging, which was used to detect ambient emissions from fluid-filled fractures, and 2) reservoir tomography, which used information about travel paths, source locations, and source parameters of micro-earthquakes to identify areas of enhanced permeability. Integration of these methods provided guidance for siting wells and served as prior constraints for reservoir models, informing forecasts of power potential and production and injection strategies aimed at minimizing temperature decline and improving overall resource productivity.

15 GEOTHERMAL ENERGY↗

NASA NTRS1975

The long term energy problem and aeronautics

The projected increase in energy consumption by transportation in general and civil aviation in particular is directly opposed to the dwindling supplies of natural petroleum crude oil currently used to produce aircraft fuels. This fact dictates the need to develop even more energy conservative aircraft and propulsion systems than are currently available and to explore the potential of alternative fuels to replace the current petroleum derived hydrocarbons. Advances in technology are described in the areas of improved component efficiency, aircraft and engine integration, control systems, and advanced lightweight materials that are needed to maximize performance and minimize fuel usage. Also, improved turbofan and unconventional engine cycles which can provide significant fuel usage reductions are described. These advancements must be accomplished within expected environmental constraints such as noise and pollution limits. Alternative fuels derived from oil shale and coal are described, and the possible technological advancements needed to use these fuels in aircraft engines are discussed and evaluated with relation to potential differences in fuel characteristics.

Rudey, R. A.↗

NASA NTRS2015

Integrated Vehicle and Trajectory Design of Small Spacecraft with Electric Propulsion for Earth and Interplanetary Missions

This paper investigates the feasibility of Earth-transfer and interplanetary mission architectures for miniaturized spacecraft using emerging small solar electric propulsion technologies. Emerging small SEP thrusters offer significant advantages relative to existing technologies and will enable U-class systems to perform trajectory maneuvers with significant Delta V requirements. The approach in this paper is unique because it integrates trajectory design with vehicle sizing and accounts for the system and operational constraints of small U-class missions. The modeling framework includes integrated propulsion, orbit, energy, and external environment dynamics and systems-level power, energy, mass, and volume constraints. The trajectory simulation environment models orbit boosts in Earth orbit and flyby and capture trajectories to interplanetary destinations. A family of small spacecraft mission architectures are studied, including altitude and inclination transfers in Earth orbit and trajectories that escape Earth orbit and travel to interplanetary destinations such as Mercury, Venus, and Mars. Results are presented visually to show the trade-offs between competing performance objectives such as maximizing available mass and volume for payloads and minimizing transfer time. The results demonstrate the feasibility of using small spacecraft to perform significant Earth and interplanetary orbit transfers in less than one year with reasonable U-class mass, power, volume, and mission durations.

Spangelo, Sara↗

DOE OSTI2025

Experimental targets for dark photon dark matter

Ultralight dark photon dark matter features distinctive cosmological and astrophysical signatures and is also supported by a burgeoning direct-detection program searching for its kinetic mixing with the ordinary photon over a wide mass range. Dark photons, however, cannot necessarily constitute the dark matter in all of this parameter space. In minimal models where the dark photon mass arises from a dark Higgs mechanism, early-Universe dynamics can easily breach the regime of validity of the low-energy effective theory for a massive vector field. In the process, the dark sector can collapse into a cosmic string network, precluding dark photons as viable dark matter. We establish the general conditions under which dark photon production avoids significant backreaction on the dark Higgs and identify regions of parameter space that naturally circumvent these constraints. After surveying implications for known dark photon production mechanisms, we propose novel models that set well-motivated experimental targets across much of the accessible parameter space. We also discuss complementary cosmological and astrophysical signatures that can probe the dark sector physics responsible for dark photon production.

Dark matter↗

DOE OSTI2020

A Combined Day-ahead and Real-time approach for Scheduling Real and Reactive power dispatch of Battery Energy Storage System

A combined day-ahead (look-ahead) and real-time optimization approach is proposed to schedule BESS real and reactive power dispatch. The look ahead scheduling agent maximizes profit and essentially performs the function of energy arbitrage by looking at forecasted prices, network constraints and BESS operating conditions to generate real power dispatch schedule. While this schedule is followed, the real time optimization agent computes an optimum reactive power set-point (for a particular objective function) using optimal power flow framework. The concepts are implemented by co-simulating legacy tools and demonstrated on a large real world distribution system. In addition to the profits from energy arbitrage, optimum reactive power set point computation results in achieving desirable network attributes like flat voltage profiles and minimizing voltage deviations from desired value.

Bhatti, Bilal A.↗

DOE OSTI2023

The Importance of Addressing Disagreements Between Nominal and Effective Treatments During Bat Mortality Minimization Validation Studies

As the wind energy industry grows, so too does our need for effective and low-cost bat mortality minimization solutions. Despite knowledge gaps in our understanding of what drives bats to collide with spinning turbines, minimization solutions have shown success during validation studies. Curtailment has been consistently effective, reducing bat mortality from 33%-79%, depending on the curtailment scenario and species present. Several validation studies have demonstrated deterrent solutions, specifically ultrasonic deterrents, to be effective, but overall, more variable compared to curtailment solutions. Further, a study combining curtailment with ultrasonic deterrents produced encouraging results, finding that adding ultrasonic deterrents to turbines that were designated to curtail, significantly reduced mortality rates compared to curtailment only turbines. Despite positive results, the strength of inference achieved with validation studies is limited by methodological constraints associated with appropriately assigning fatalities to treatments. Because of the temporal separation between when a bat collides with a turbine and when it is discovered during a ground-based carcass survey, we must assign carcasses to a treatment that ran during the prior night(s). This process may introduce errors at multiple stages. First, for studies that rotate treatments among turbines, mortality surveyors must be confident that carcasses are 'fresh' such that mortalities are correctly assigned to the treatment from the previous night(s). Second, we must reconcile any misalignments between how we assign treatments and how we implement treatments (e.g., turbines assigned with a deterrent treatment may be implemented as another treatment when deterrent devices are not operating as designed). Finally, for curtailment solutions, it is critical to recognize that measured effects are a function of not just the treatment as implemented but the proportion of the night the treatment is realized (e.g., if wind speeds are greater than the curtailment treatment cut-in speed for the entire night, we cannot expect there to me any differences in mortality reduction relative to control turbines). Using a dataset collected between June and October 2017, that rotated 3 treatments (Deterrent Only, 5 m/s Curtail only, and 5 m/s Curtail & Deterrent) and 1 control condition across 16 turbines each night, we explored the importance and implications of accounting for potential errors in assigning fatalities to treatments. We present preliminary results comparing the mortality associated with error-corrected treatments and control conditions highlighting how the measured effect of a treatment (mortality) greatly depends on site specific implementation.

bats↗

DOE OSTI2024

Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.

data processing↗

DOE OSTI2023

Process-based cost estimation framework for assessing economic viability of environmentally and socially sustainable rare earth element feedstocks

Rare Earth Elements (REEs) are critical raw material inputs that are required to enable the energy transition. Constraints on the U.S. supply of conventional REE feedstocks and the desire to diversify U.S. reliance on foreign supply chains have motivated the pursuit of REE recovery from unconventional feedstocks including waste products. Recovery of REEs from unconventional sources is also motivated by environmental and social considerations, including the potential to offset new mining activity and subsidize the remediation of REE-containing wastes from coal, natural gas, and other mineral extraction activities. Sourcing REEs from unconventional feedstocks would reduce supply chain constraints and minimize the environmental impacts of REE extraction, but current processes to exploit these feedstocks have uncertain technical and economic performance and the processes have not been demonstrated at scale. This work aims to reduce uncertainty in evaluating the performance of new REE production pathways. A database of operating and capital expenses for REE recovery and establish consistent process unit costs for common stages in the conventional supply chain are developed. Market prices are used to develop well-defined methods for determining product values for a diverse set of products that can be generated (e.g. oxalates, alloys, end-use products such as magnets) but are not typically considered in technoeconomic analyses. Finally, to provide insight on the effects of economies of scale and feedstock purity on capital and operating costs, process unit level cost functions relating total costs per kilogram of REE produced are reported. These tools can be applied to assess and facilitate scale-up of REE production from diverse sources of REEs.

Fritz, Alison↗

DOE OSTI2020

Advances in Kriging-Based Autonomous X-Ray Scattering Experiments

Autonomous experimentation is an emerging paradigm for scientific discovery, wherein measurement instruments are augmented with decision-making algorithms, allowing them to autonomously explore parameter spaces of interest. We have recently demonstrated a generalized approach to autonomous experimental control, based on generating a surrogate model to interpolate experimental data, and a corresponding uncertainty model, which are computed using a Gaussian process regression known as ordinary Kriging (OK). We demonstrated the successful application of this method to exploring materials science problems using x-ray scattering measurements at a synchrotron beamline. Here, we report several improvements to this methodology that overcome limitations of traditional Kriging methods. The variogram underlying OK is global and thus insensitive to local data variation. We augment the Kriging variance with model-based measures, for instance providing local sensitivity by including the gradient of the surrogate model. As with most statistical regression methods, OK minimizes the number of measurements required to achieve a particular model quality. However, in practice this may not be the most stringent experimental constraint; e.g. the goal may instead be to minimize experiment duration or material usage. We define an adaptive cost function, allowing the autonomous method to balance information gain against measured experimental cost. We provide synthetic and experimental demonstrations, validating that this improved algorithm yields more efficient autonomous data collection.

36 MATERIALS SCIENCE↗

NASA NTRS1997

Thrust Enhancement in Hypervelocity Nozzles by Chemical Catalysis

In the hypersonic flight regime, the air-breathing supersonic combustion ramjet (scramjet) has been shown to be a viable propulsion system. The current designs of scramjet engines provide performance benefits only up to a Mach number of 14. Performance losses increase rapidly as the Mach number increases. To extend the applicability of scram'jets beyond Mach 14, research is being conducted in the area of inlet and wave drag reduction, skin-friction and heat-transfer reduction, nozzle loss minimization, low-loss mixing, and combustion enhancement. For high Mach number applications, hydrogen is the obvious fuel choice because of its high energy content per unit mass in comparison with conventional fuels. These flight conditions require engines to operate at supersonic internal velocities, high combustor temperatures, and low static pressures. The high static temperature condition enhances the production of radicals such as H and OH, and the low-pressure condition slows the reaction rates, particularly the recombination reactions. High-temperature and low-pressure constraints, in combination with a small residence time, result in a radical-rich exhaust gas mixture exiting the combustor. At high Mach number conditions (due to low residence time), H and OH do not have enough time to recombine ; thus, a significant amount of energy is lost as these high-energy free radical are exhausted. The objective of the present study is to conduct a flowfield analysis for a typical nozzle geometry for NASP-type vehicle to assess for thrust enhancement in hypervelocity nozzles by substituting small amount of phosphine for hydrogen.

Singh, D. J.↗

DOE OSTI2023

Simulating Atomic Dark Matter in Milky Way Analogs

Dark sector theories naturally lead to multicomponent scenarios for dark matter where a subcomponent can dissipate energy through self-interactions, allowing it to efficiently cool inside galaxies. We present the first cosmological hydrodynamical simulations of Milky Way analogs where the majority of dark matter is collisionless cold dark matter (CDM) but a subcomponent (6%) is strongly dissipative minimal atomic dark matter (ADM). The simulations, implemented in GIZMO and utilizing FIRE-2 galaxy formation physics to model the standard baryonic sector, demonstrate that the addition of even a small fraction of dissipative dark matter can significantly impact galactic evolution despite being consistent with current cosmological constraints. We show that ADM gas with roughly standard model–like masses and couplings can cool to form a rotating “dark disk” with angular momentum closely aligned with the visible stellar disk. The morphology of the disk depends sensitively on the parameters of the ADM model, which affect the cooling rates in the dark sector. The majority of the ADM gas gravitationally collapses into dark “clumps” (regions of black hole or mirror star formation), which form a prominent bulge and a rotating thick disk in the central galaxy. These clumps form early and quickly sink to the inner ∼kiloparsec of the galaxy, affecting the galaxy’s star formation history and present-day baryonic and CDM distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2016

Application of Interval Predictor Models to Space Radiation Shielding

This paper develops techniques for predicting the uncertainty range of an output variable given input-output data. These models are called Interval Predictor Models (IPM) because they yield an interval valued function of the input. This paper develops IPMs having a radial basis structure. This structure enables the formal description of (i) the uncertainty in the models parameters, (ii) the predicted output interval, and (iii) the probability that a future observation would fall in such an interval. In contrast to other metamodeling techniques, this probabilistic certi cate of correctness does not require making any assumptions on the structure of the mechanism from which data are drawn. Optimization-based strategies for calculating IPMs having minimal spread while containing all the data are developed. Constraints for bounding the minimum interval spread over the continuum of inputs, regulating the IPMs variation/oscillation, and centering its spread about a target point, are used to prevent data over tting. Furthermore, we develop an approach for using expert opinion during extrapolation. This metamodeling technique is illustrated using a radiation shielding application for space exploration. In this application, we use IPMs to describe the error incurred in predicting the ux of particles resulting from the interaction between a high-energy incident beam and a target.

Crespo, Luis G.↗

DOE OSTI2023

Optimal gas cooling with minimal aero-opticaldistortion for next generation high-average-power lasers (Progress report, Year 2)

Next-generation lasers that combine high-peak-power ultrashort pulses with high repetition rates have the potential to efficiently deliver the high-average-power outputs required for inertial fusion energy generation, laser-based particle acceleration, and to generate compact secondary x- and 𝛾-ray radiation sources, among others. The combination of long gain length with high surface-to-volume ratio to remove residual heat makes gas-cooled multi-slab amplifier heads an inherently aperture- and average power scalable technology that enables this new class of solid-state lasers, and their thermal management becomes the most pressing technical challenge. As the index-of refraction depends on the gas density, heat removal from the slab surfaces unavoidably entails scattering of propagated light from regions of high temperature fluctuations. The requirement to maximize convective heat extraction from the gain medium under the constraint of minimum optical aberration of the beam renders amplifier slab cooling a technological challenge at the intersection of aero-optics, fluid-mechanics and heat transfer. The goal of this research is to leverage computational fluid dynamics and aero optics simulations of different levels of fidelity to devise a numerical modeling and optimization framework for gas-cooled multi-slab amplifiers. The project will be conducted in close collaboration with the Advanced Photon Technologies Group at Lawrence Livermore National Laboratory, where a gas-cooled test stand for laser materials and thermal management structures will be developed and installed. The final goal of the collaborative effort is to manufacture and benchmark a physical prototype of an numerically optimized amplifier head design. Measurement data on solid-state and thermo-optical distortions will be used for the validation of the numerical models. The key technical challenge in this multi-objective design problem is that of balancing optimal heat removal with minimal optical distortion. To facilitate computationally efficient design optimization and, at the same time, deepen our basic understanding of the interaction of light with turbulence, a complementary study that combines high and low-fidelity flow simulations and aero-optical models is proposed. Along the lines of these two objectives and solution strategies, the project is organized into two thrusts.

42 ENGINEERING↗

NASA NTRS1991

Advances in modeling the pressure correlation terms in the second moment equations

In developing turbulence models, various model constraints were proposed in an attempt to make the model equations more general (or universal). The most recent of these are the realizability principle, the linearity principle, the rapid distortion theory, and the material indifference principle. Several issues are discussed concerning these principles and special attention is payed to the realizability principle. Realizability (defined as the requirement of non-negative energy and Schwarz' inequality between any fluctuating quantities) is the basic physical and mathematical principle that any modeled equation should obey. Hence, it is the most universal, important and also the minimal requirement for a model equation to prevent it from producing unphysical results. The principle of realizability is described in detail, the realizability conditions are derived for various turbulence models, and the model forms are proposed for the pressure correlation terms in the second moment equations. Detailed comparisons of various turbulence models with experiments and direct numerical simulations are presented. As a special case of turbulence, the two dimensional two-component turbulence modeling is also discussed.

Shih, Tsan-Hsing↗

NASA NTRS1992

Advances in modeling the pressure correlation terms in the second moment equations

Shih, Tsan-Hsing↗