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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

Optimizing Requirements Decisions with KEYS

Recent work with NASA's Jet Propulsion Laboratory has allowed for external access to five of JPL's real-world requirements models, anonymized to conceal proprietary information, but retaining their computational nature. Experimentation with these models, reported herein, demonstrates a dramatic speedup in the computations performed on them. These models have a well defined goal: select mitigations that retire risks which, in turn, increases the number of attainable requirements. Such a non-linear optimization is a well-studied problem. However identification of not only (a) the optimal solution(s) but also (b) the key factors leading to them is less well studied. Our technique, called KEYS, shows a rapid way of simultaneously identifying the solutions and their key factors. KEYS improves on prior work by several orders of magnitude. Prior experiments with simulated annealing or treatment learning took tens of minutes to hours to terminate. KEYS runs much faster than that; e.g for one model, KEYS ran 13,000 times faster than treatment learning (40 minutes versus 0.18 seconds). Processing these JPL models is a non-linear optimization problem: the fewest mitigations must be selected while achieving the most requirements. Non-linear optimization is a well studied problem. With this paper, we challenge other members of the PROMISE community to improve on our results with other techniques.

requirements↗
DOE OSTI2024

Revenue Analysis of Stationary and Transportable Battery Storage for Power Systems: A Market Participant Perspective

The power system faces a growing need for increased transmission capacity and reliability with the rising integration of renewable energy resources. To tackle this challenge, Battery Energy Storage Systems (BESSs) prove effective in enhancing grid capacity and relieving transmission congestion. This paper focuses on the PJM market, conducting a thorough revenue analysis to identify and characterize highly profitable nodes for BESS market participants. A comparison between stationary and transportable BESSs reveals that the transportable BESSs can generate higher potential revenue in energy and regulation markets. Based on these findings, we propose an optimal placement algorithm to support market participants in selecting strategic sites for BESS installation, validated with real PJM market data. This paper provides valuable insights for navigating market-based power system participants and promoting the effective integration of BESSs.

25 ENERGY STORAGE↗
NASA NTRS1975

Concept selection and analysis of large wind generator systems

The increasing need to develop alternative energy sources has renewed interest in the use of wind energy for the generation of utility quality electricity. This paper discusses a program to evolve a preliminary design of a cost competitive large wind generator system. An examination of a number of technically feasible alternative wind energy configurations is reported, and the rationale used in selecting the preferred system concept is presented. In addition, preliminary results of an optimization study conducted on the preferred concept are summarized. These show that considerable latitude in the selection of the system design parameters is possible. This permits design decisions to be based on other important factors such as development risk and the suitability of common component designs for systems with different power ratings.

Meier, R. C.↗
NASA NTRS1985

Variability in the high energy gamma ray emission from Cyg X-3 over a two-year period (1983 - 1984) at E 4 x 10(11) eV

Cygnus X-3 is observed to emit gamma rays with energies in excess of 4 x 10 to the 11th power eV during two out of 9 observational categories over an 18 month time span. The emissions are observed at the 0.6 phase of the characteristic 4.8 hr light curve for this binary system. We estimate a peak flux at phase 0.6 of 5 x 10 to the minus 10th power photons cm-2s-1 at a software threshold of 8 x 10 to the 11th power eV for Oct/Nov 1983. A flux for the June 84 effect cannot be reliably calculated at present due to lack of Monte Carlo simulations for the energy range and spectral region. For the other 7 observational categories the observations are consistent with zero source emission. The light curve would appear to be variable on a time scale of a couple of weeks at these categories. Selection of compact images in accordance with Monte Carlo simulations combined with empirical optimization techniques have led to an enriched gamma ray light curve for the Oct/Nov 1983 data. Selection on the basis of shower orientation, however, has not led to any notable enhancement of the gamma ray content. Individual Cherenko images can be reliably sorted on an event by event basis into either proton-induced or photon-induced showers.

Cawley, M. F.↗
DOE OSTI2018

Selective Recovery of Critical Materials from Geothermal Fluid

This project, funded by the DOE Small Business Voucher program, assisted the partner with the development of ion-imprinted adsorbents for the selective extraction of rare earth elements (REE) from geothermal brines. This effort seeks to utilize a currently untapped resource thus diversifying the U. S. REE market. The initial stage of the program focused on the adsorbent developed by partner and optimization of the adsorbent. The adsorbent was based upon an ion imprinted ligand that was copolymerized with a crosslinker to generate the REE selectivity. During this task, the adsorbents were irradiated via electron beam at the NEO Beam Electron Beam Crosslinking Facility (Mercury Plastics, Middlefield, OH) to induce further crosslinking. The irradiation crosslinked adsorbents exhibited no difference in the Fourier transform infrared spectroscopic (FTIR) analysis suggesting inefficiency in the crosslinking. In the later stage of the effort, a new method was proposed and studied at ORNL involving a new partnership between the partner and a commercial polymer vender. This resulted in a new material being developed which allows the partner to utilize a commercial support and integrate the synthesis into a production-ready product stream. This will enhance the route to commercialization for the partner resulting in a quicker market penetration for the product. The new adsorbent exhibits selectivity for REE over transition metals commonly found within geothermal brines. Further optimization is required for enhanced selectivity, capacity, and intra-lanthanide separations.

58 GEOSCIENCES↗
DOE OSTI2020

Closed-loop optimization of fast-charging protocols for batteries with machine learning

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years. Furthermore, both large parameter spaces and high sampling variability necessitate a large number of experiments. As such, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users. We combine two key elements to reduce the optimization cost: an early-prediction model, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

25 ENERGY STORAGE↗
DOE OSTI2022

Data Driven Optimization Framework for Volt-age Regulation in Distribution Systems

This letter proposes a data-driven optimization framework for voltage regulation problems to address the challenge of model inaccuracy and parameter varying. To achieve online voltage optimization, the recursive kernel regression and interior point methods are integrated. The IEEE 123-Bus system and EPRI Ckt5 feeder are selected to validate the effectiveness of the proposed data-driven optimization framework. The proposed method is also compared with a linear function based method.

Hong, Tianqi↗
NASA NTRS1993

Trajectory optimization for a National Launch System vehicle

A trajectory design process is presented for a proposed National Launch System (NLS) vehicle configuration. A software trajectory planner was developed to generate near optimal pitch plane trajectories for variable mission plans, variable launch site selections, and last minute wind conditions at the time of launch. In addition, the trajectory planner performs in-flight near optimal trajectory redesign in the event of an engine-out or unexpected wind dispersions. The trajectory planner iteratively simulates trial trajectories defined by variables corresponding to a parameterized trajectory shape. The trajectory planner optimizes these trajectory parameters according to the fuel used to realize the trajectories. For prelaunch scenarios, the trajectory planner generated near optimal trajectories of consistent fuel performance irrespective of the winds encountered at the launch site. In-flight trajectory redesigns were also shown to be effective in fulfilling the mission plan and preserving the structural integrity of the vehicle. The in-flight redesign results indicate that closed-loop guidance in the early stages of ascent is highly effective in accommodating engine failures or wind dispersions. All trajectory designs were verified using a 6DOF simulation with flight controllers.

Chen, Eugene S.↗
NASA NTRS1990

Integrated topology and shape optimization in structural design

Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.

Bremicker, M.↗
DOE OSTI2018

Optimizing searches for electromagnetic counterparts of gravitational wave triggers

With the detection of a binary neutron star system and its corresponding electromagnetic counterparts, a new window of transient astronomy has opened. Due to the size of the sky localization regions, which can span hundreds to thousands of square degrees, there are significant benefits to optimizing tilings for these large sky areas. The rich science promised by gravitational wave astronomy has led to the proposal for a variety of proposed tiling and time allocation schemes, and for the first time, we make a systematic comparison of some of these methods. We find that differences of a factor of 2 or more in efficiency are possible, depending on the algorithm employed. For this reason, with future surveys searching for electromagnetic counterparts, care should be taken when selecting tiling, time allocation, and scheduling algorithms to optimize counterpart detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Precise Motion Control of Hybrid Hydraulic Electric Architecture (HHEA)

Off-highway heavy-duty vehicles have been long-standing users of hydraulic systems for power transmission and control. However, traditional hydraulic systems suffer from significant energy losses which lead to increased operating costs and a larger carbon footprint due to higher CO2 emissions. Improving the efficiency of these mobile machines is crucial not only for reducing their environmental impact but also for saving billions of dollars in operating costs. Currently, the state-of-the-art Load Sensing Architecture uses throttling valves for control, which significantly reduces its efficiency and does not recuperate energy from over-running loads. Researchers have developed several architectures such as Common Pressure Rail systems, Displacement Control, STEAM, and Electrohydraulic Architecture to improve the efficiency of off-road mobile machines. However, each of these architectures has its drawbacks. To increase system efficiency and take advantage of electrification benefits, our research group has developed a novel Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA can significantly improve efficiency, decrease the size of electrical components, and maintain control performance. This new architecture has the potential to revolutionize the off-highway mobile machine industry and lead to a more sustainable future. The HHEA uses a set of common pressure rails to provide the majority of power to the actuators via power-dense hydraulics and uses electric motors for precise control and power modulation. In the context of off-road mobile machines, energy savings are undoubtedly important but it is equally important to consider the machines’ ability to perform tasks with precision and accuracy according to given commands. Therefore, precise motion control is of utmost importance to maintain the utility of Hybrid Hydraulic-Electric Architecture (HHEA). The HHEA presents a unique challenge to motion control due to the discrete pressure changes that occur when the system switches between selected pressure rails. These changes are made to minimize system inefficiencies or to keep the system within the torque capability of the electric motor. Hence, it is important to solve the motion control challenges for HHEA. This thesis aims at developing an effective motion control strategy for HHEA. The dissertation presents a two-tiered control strategy for HHEA, comprising a high-level and a low-level controller. The primary responsibility of the high- level controller is to optimize energy efficiency by making informed pressure rail selections. On the other hand, the low-level controller is focused on achieving precise motion control of the HHEA, which is crucial for realizing the desired reference trajectories. To achieve this, the low-level controller utilizes a passivity-based backstepping integral controller as the nominal control, which handles the motion control between two pressure rail switches. Additionally, a separate least norm controller is utilized as a transition controller to manage motion control during pressure rail transitions. The effectiveness of the combined control strategy is demonstrated through experiments conducted on two hardware-in-the-loop testbeds. Furthermore, the HHEA is installed on the boom and stick actuators of a backhoe arm to build a Human-in-the-Loop system that a human operator can control. A real-time rail switching algorithm is developed to determine pressure rail switching based on present duty cycle information from the operator. Modifications have been made to the human-machine interface to achieve more intuitive control. Modifications include performing control in the task-oriented coordinates, incorporating pressure feedback to enhance control with physical interaction, and using velocity field control to simplify multi-degree-of-freedom tasks and to enable novice operators to perform them with reduced risk, improved efficiency, and productivity. The research in this dissertation makes significant contributions to the field of off-road mobile machine control, providing a novel and effective control strategy for the HHEA, and demonstrating the potential for simplified machine operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Highly efficient and selective pressure-assisted photon-induced polymerization of styrene

The polymerization process of condensed styrene to produce polystyrene as an industrially important polymeric material was investigated using a novel approach by combining external compression with ultraviolet radiation. The reaction evolution was monitored as a function of time and the reaction products were characterized by in situ Fourier transform infrared spectroscopy. By optimizing the loading pressures, we observed highly efficient and selective production of polystyrene of different tacticities. Specifically, at relatively low loading pressures, infrared spectra suggest that styrene monomers transform to amorphous atactic polystyrene (APS) with minor crystalline isotactic polystyrene. In contrast, APS was found to be the sole product when polymerization occurs at relatively higher loading pressures. The time-dependent reaction profiles allow the examination of the polymerization kinetics by analyzing the rate constant and activation volume as a function of pressure. As a result, an optimized pressure condition, which allows a barrierless reaction to proceed, was identified and attributed to the very desirable reaction yield and kinetics. Finally, the photoinitiated reaction mechanism and the growth geometry of the polymer chains were investigated from the energy diagram of styrene and by the topology analysis of the crystal styrene. This study shows strong promise to produce functional polymeric materials in a highly efficient and controlled manner.

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

Atomic Layer Deposition Overcoating Improves Catalyst Selectivity and Longevity in Propane Dehydrogenation

Propylene, a precursor for commodity chemicals and plastics, is produced by propane dehydrogenation (PDH). An increase in PDH yield via added catalyst activity, lifetime, or selectivity represents significant energy and economic savings. Using Pt dispersed on Al2O3 extrudate supports as a commercially relevant model system, we demonstrate that atomic layer deposition (ALD) metal oxide overcoats, used to tailor metal-active sites, can increase PDH yield and selectivity. We investigate the interplay of Pt loading, ALD overcoat thickness, and Al 2 O 3 support surface area on PDH activity, selectivity, and catalyst stability to show that applying a 6-8 A thick layer of Al 2 O 3 on low-surface area Al 2 O 3 supports of similar to 90 m 2 /g surface area yields the optimal combination of stability and activity, while increasing propylene selectivity from 91 to 96%. Increased stability upon steaming deactivation occurs because the Al 2 O 3 overcoat prevents the Pt nanoparticles from sintering. We speculate that the ALD overcoat selectively binds to the undercoordinated sites on the Pt nanoparticles, while leaving the more selective terrace sites available for dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Candidate Species Selection: Cultural and Photosynthetic Aspects

Cultural information is provided for a data base that will be used to select candidate crop species for a controlled ecological life support system (CELSS). Lists of food crops which will satisfy most nutritional requirements of humans and also fit within the scope of cultural restrictions that logically would apply to a closed, regenerating system were generated. Cultural and environmental conditions that will allow the most rapid production of edible biomass from candidate species in the shortest possible time are identified. Cultivars which are most productive in terms of edible biomass production by (CE) conditions, and which respond to the ever-closed approach to optimization realized by each shortened production cycle are selected. The experimental approach with lettuce was to grow the crop hydroponically in a growth chamber and to manipulate such variables as light level and duration, day/night temperature, and nutrient form and level in the solution culture.

Mitchell, C. A.↗
NASA NTRS1997

CONDUIT: A New Multidisciplinary Integration Environment for Flight Control Development

A state-of-the-art computational facility for aircraft flight control design, evaluation, and integration called CONDUIT (Control Designer's Unified Interface) has been developed. This paper describes the CONDUIT tool and case study applications to complex rotary- and fixed-wing fly-by-wire flight control problems. Control system analysis and design optimization methods are presented, including definition of design specifications and system models within CONDUIT, and the multi-objective function optimization (CONSOL-OPTCAD) used to tune the selected design parameters. Design examples are based on flight test programs for which extensive data are available for validation. CONDUIT is used to analyze baseline control laws against pertinent military handling qualities and control system specifications. In both case studies, CONDUIT successfully exploits trade-offs between forward loop and feedback dynamics to significantly improve the expected handling, qualities and minimize the required actuator authority. The CONDUIT system provides a new environment for integrated control system analysis and design, and has potential for significantly reducing the time and cost of control system flight test optimization.

Tischler, Mark B.↗
NASA NTRS2000

Flight Control Role in RLV Configuration Development

A new optimization technique was used to aide in the selection of aerodynamic surfaces and Thrust Vectoring Control (TVC) based on maximizing control margin during ascent and entry portions of the trajectory. In order to meet the mass fraction requirement of RLV (Reusable Launch Vehicle), every substructure needed to be carefully designed to minimize the dry mass. The trajectory was designed to deliver the payload required for each mission subject to thermal and structural constraints. At each point on the trajectory the angle of attack and Mach number pair was used to calculate the control power required to trim and to stabilize the vehicle. The new optimization technique was based on finding the configuration that minimizes the control power peaks along the entire trajectory.

Youssef, Hussein↗
DOE OSTI2021

Developing a Drilling Optimization System for Improved Overall Rate of Penetration in Geothermal Wells

Geothermal energy is renewable, reliable and environmentally friendly source of energy. The major cost in the development of geothermal wells is the actual drilling of the wells. The main objective of this paper is to introduce a new real-time drilling optimization system designed for granite formation to reduce the overall drilling cost. In this study, a drilling optimization system is verified using drilling data from Utah-Forge well 58-32. The drilling optimization system used the Utah-Forge well 58-32 data to achieve real-time unconfined compressive strength (UCS). Based on the UCS value from the previous feet, the system simulates the ROP for the next drilling feet. The drilling optimization system utilizes the Differential Evolution Algorithm (DEA), which is a metaheuristic method to search the space of solution, to find the best operating parameters (i.e. WOB and RPM) for the next drilling foot. The optimization algorithm takes a maximum cutter temperature into account as a constraint and avoids the accelerated wear. The developed drilling optimization system improves ROP responses and reduces the drilling cost of geothermal wells. The simulated ROP results from the system show a good agreement with the ROP from Utah-Forge well 58-32 drilling data. The drilling time before and after optimization for both intervals were presented.

15 GEOTHERMAL ENERGY↗

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