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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Optimizing Postural Control Assessment in Astronauts and Head-Down Bedrest Subjects

In space, astronauts undergo physiological adaptations, such as changes in sensorimotor processing, to acclimate to microgravity conditions. However, these adaptations pose challenges upon astronauts’ return to Earth, particularly in postural control. Astronauts struggle with balance and coordination during the early post-flight period. Understanding these adaptations and their implications is key for optimizing astronaut health and performance, especially in anticipation of upcoming Artemis lunar missions. Head-down bedrest (HDBR) is a ground-based spaceflight analog that allows for additional research to be conducted into this adaptation and recovery period to test potential countermeasures before spaceflight. This research aims to delve into the assessment of postural control in both HDBR subjects and astronauts, providing insights essential for mission preparedness and the development of effective countermeasures.

H E Gustafson↗
DOE OSTI2016

WE-AB-207B-11: Optimizing Tumor Control Probability in Radiation Therapy Treatment - Application to HDR Cervical Cancer

Purpose: The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor-control-probability(TCP) with an acceptable normal-tissue-complication probability(NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. We design treatment plans that optimize TCP directly and contrast them with the clinical dose-based plans. PET image is incorporated to evaluate gain in TCP for dose escalation. Methods: We build a nonlinear mixed integer programming optimization model that maximizes TCP directly while satisfying the dose requirements on the targeted organ and healthy tissues. The solution strategy first fits the TCP function with a piecewise-linear approximation, then solves the problem that maximizes the piecewise linear approximation of TCP, and finally performs a local neighborhood search to improve the TCP value. To gauge the feasibility, characteristics, and potential benefit of PET-image guided dose escalation, initial validation consists of fifteen cervical cancer HDR patient cases. These patients have all received prior 45Gy of external radiation dose. For both escalated strategies, we consider 35Gy PTV-dose, and two variations (37Gy-boost to BTV vs 40Gy-boost) to PET-image-pockets. Results: TCP for standard clinical plans range from 59.4% - 63.6%. TCP for dose-based PET-guided escalated-dose-plan ranges from 63.8%–98.6% for all patients; whereas TCP-optimized plans achieves over 91% for all patients. There is marginal difference in TCP among those with 37Gy-boosted vs 40Gy-boosted. There is no increase in rectum and bladder dose among all plans. Conclusion: Optimizing TCP directly results in highly conformed treatment plans. The TCP-optimized plan is individualized based on the biological PET-image of the patients. The TCP-optimization framework is generalizable and has been applied successfully to other external-beam delivery modalities. A clinical trial is on-going to gauge the clinical significance. Partially supported by the National Science Foundation.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

The uncertainty threshold principle - Some fundamental limitations of optimal decision making under dynamic uncertainty

This note shows that the optimal control of dynamic systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic optimal control example, it is shown that the infinite horizon solution does not exist if the parameter uncertainty exceeds a certain quantifiable threshold; we call this the uncertainty threshold principle. The philosophical and design implications of this result are discussed.

Athans, M.↗
NASA NTRS1977

The Uncertainty Threshold Principle: Some Fundamental Limitations of Optimal Decision Making Under Dynamic Uncertainity

This note shows that the optimal control of dynamic systems with uncertain parameters has certain limitations. In particular, by means of a simple scalar linear-quadratic optimal control example, it is shown that the infinite horizon solution does not exist if the parameter uncertainty exceeds a certain quantifiable threshold; we call this the uncertainty threshold principle. The philosophical and design implications of this result are discussed.

Athans, M.↗
NASA NTRS1982

An investigation of quasi-inertial attitude control for a solar power satellite

An efficient means, a quasi-inertial attitude mode, is developed for maintaining the normal solar orientation of a space satellite for power collection in a synchronous orbit. Formulae are presented which establish the basic parametric properties for ideal quasi-inertial attitude and phasing. An active control system is necessary to compensate for the energy loss since energy dissipation in widely oscillating flexible bodies produces an instability of the quasi-inertial attitude in the sense that the spacecraft will tumble at the orbit rate. A fixed terminal time and state optimal control problem is formulated and an algorithm for determining the optimal control as a means for the periodical attitude and phase compensation is developed. The vehicle orientation affected by internal disturbance (structural flexibility) and external disturbances (e.g., drag forces) is maintained by a specialized controller design.

Juang, J.-N.↗
DOE OSTI2024

Robust Quantum Control via Multipath Interference for Thousandfold Phase Amplification in a Resonant Atom Interferometer

We introduce a novel technique for enhancing the robustness of light-pulse atom interferometers against the pulse infidelities that typically limit their sensitivities. The technique uses quantum optimal control to favorably harness the multipath interference of the stray trajectories produced by imperfect atom-optics operations. We apply this method to a resonant atom interferometer and achieve thousandfold phase amplification, representing a 50-fold improvement over the performance observed without optimized control. Moreover, we find that spurious interference can arise from the interplay of spontaneous emission and many-pulse sequences and demonstrate optimization strategies to mitigate this effect. Given the ubiquity of spontaneous emission in quantum systems, these results may be valuable for improving the performance of a diverse array of quantum sensors. We anticipate our findings will significantly benefit the performance of matter-wave interferometers for a variety of applications, including dark matter, dark energy, and gravitational wave detection.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Adjoint-Based Minimization of X-59 Sonic Boom Noise Via Control Surfaces

A multidisciplinary design optimization methodology to directly minimize the ground-level noise generated by a supersonic aircraft's sonic boom is presented. A gradient-based optimizer is coupled with a Cartesian Euler flow solver and an atmospheric propagation tool to forge a unique design capability. Adjoint formulations for both the flow solver and propagation tool are also coupled to provide sensitivities in an efficient manner. The design method is demonstrated on the X-59 Low-Boom Flight Demonstrator by optimizing control surface deflections to improve ground-level noise while maintaining trimmed cruise flight. Two noise minimization examples and a noise maximization are presented. All optimized designs result in measurable improvement in the ground-level noise objective. Extensive surveys of the design space confirm that the optimization method is effective in finding a local optimum. Moreover, repeated application of the method with varying initial design points also demonstrates the robustness of the method.

ARMD↗
NASA NTRS1971

Design of optimal probing signals for vector parameter estimation.

In the design of optimal inputs or probing signals for parameter estimation, it is more natural to consider functions of the Fisher information matrix as the criterion of optimality instead of some function of the error covariance matrix. The input which maximizes the Fisher information measure for efficient estimation of a scalar parameter also provides the minimum error variance. The information is thus a logical choice for the optimality criterion in scalar problems. No such obvious choice is apparent for vector parameter estimation. A number of performance measures are examined and compared in the present study, and a useful criterion is selected. The design of an optimal probing signal using this criterion is shown to be equivalent to an optimal control problem in which certain equality constraints must be satisfied. This problem may be solved by conventional techniques of deterministic or stochastic optimal control.

Nahi, N. E.↗
DOE OSTI2017

Power control system modification and simulation of CPR1000 - 181

Due to development of electric power system, the proportion of nuclear power and its needs for load follow operation have become large. Then there would be higher requirements to the power control ability of the nuclear power system. The axial power distribution may change a lot in the operation process and be affected by many factors. In particular, as the power change is performed within a load follow maneuver, several modifications occur in the core from a neutronic view point: the fuel and moderator temperature change, the xenon concentration and distribution are modified, the power distribution skewed axially, etc. These changes need to be adequately counterbalanced to keep both the core critical and the power distribution acceptable. The traditional approach in pressurized water reactors (PWRs) is compensating for the reactivity change due to the power variation by adjusting the soluble boron concentration and moving a limited number of control banks. However, dilution/boronation strategy becomes expensive for short time changes and leads to large volume of liquid effluent, so it is eager about a capability to perform load follow operation without changing soluble boron concentration. CPR1000, one of the main reactor types in China national development, is taken an example in this paper. It adopts a control method called Mode G, using G banks, N banks, R bank and soluble boron to perform the load follow control. According to the analysis of the physics and thermal principle, a two-node dynamic function model was built, putting the coupling coefficient and mutual influence into consideration. By the calculation of these transient parameter values which are acquired by the steady-state calculation of single channel, the core system model of CPR1000 is established. In order to carry out the load follow operation without the boron adjustment, named as BTP mode, the control banks were regrouped to control the average temperature by M banks and axial offset by AO bank. After that, the average temperature control system (M banks control system) and the axial offset control system (AO bank control system) are built. When the optimal control system is connected to the core model simulation platform, the BTP mode load follow operation of the modified CPR1000 is simulated in the end of the paper. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Autonomous Eco-Driving with Traffic Light and Lead Vehicle Constraints: An Application of Best Constrained Interpolation

Eco-Driving is a critical technology for improving automotive transportation efficiency. It is achieved by modifying the driving trajectory over a particular route to minimize required propulsion energy. Eco-Driving can be approached as an optimal control problem subject to driving constraints such as traffic lights and positions of other vehicles. Best interpolation in a strip is a problem in approximation theory and optimal control. The solution to this problem is a cubic spline. In this research, we demonstrate the connection between Eco-Driving and best interpolation in the strip. By exploiting this connection, we are able to generate optimal Eco-Driving trajectories that could be driven with an autonomous system. Using the simulation tool FASTSim, we can evaluate the trajectories using conventional, hybrid electric, and fully electric vehicle models. Our results quantify the energy efficiency improvements that can be achieved with the proposed approach.

Mahmoud, Yara Hazem↗
DOE OSTI2022

Autonomous Eco-Driving with Traffic Light and Lead Vehicle Constraints: An Application of Best Constrained Interpolation

Eco-Driving is a critical technology for improving automotive transportation efficiency. It is achieved by modifying the driving trajectory over a particular route to minimize required propulsion energy. Eco-Driving can be approached as an optimal control problem subject to driving constraints such as traffic lights and positions of other vehicles. Best interpolation in a strip is a problem in approximation theory and optimal control. The solution to this problem is a cubic spline. In this research, we demonstrate the connection between Eco-Driving and best interpolation in the strip. By exploiting this connection, we are able to generate optimal Eco-Driving trajectories that could be driven with an autonomous system. Using the simulation tool FASTSim, we can evaluate the trajectories using conventional, hybrid electric, and fully electric vehicle models. Our results quantify the energy efficiency improvements that can be achieved with the proposed approach.

Mahmoud, Yara Hazem↗
DOE OSTI2016

Optimization of Variable Speed Chiller Plants: Frank M. Johnson Jr. Federal Building and U.S. Courthouse, Montgomery, Alabama

This report is divided into five sections. The first section describes the background and opportunity for the Control Optimization System for Chiller Plant technology to reduce space cooling energy consumption at U.S. General Services Administration (GSA) facilities with centrifugal chiller plants containing multiple water-cooled chillers. The second section discusses the new technology, how it may reduce energy consumption, and introduces the demonstration location. The third section provides a detailed description of the demonstration facility and the configuration of the technology at the demonstration facility. The third section also provides a detailed overview of the approach used to assess the performance of the technology and how the chiller plant was monitored. The fourth section presents the results of the monitoring activity, documents performance and resulting energy savings, and presents the results of a life-cycle cost analysis. The fourth section also presents additional opportunities to further improve the performance of the chiller plant with control optimization, based on observations and lessons learned. The final section draws conclusions from the demonstration results and projects how GSA may best benefit from the technology’s targeted deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Optimising response to an introduction of African swine fever in wild pigs

African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the United States, invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on the size of the control areas required to rapidly eliminate the ASFv in wild pigs and how this area should change with management constraints and local ecology is needed to optimize response planning. We developed a spatially explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in Southeastern United States. We simulated ASFv spread and determined the optimal response area (reported as the radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv was detected relative to the true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly) and wild pig densities. Large radii for response areas (14 km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions, the ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within 1 year. The results highlight the importance of adjusting response plans based on local ecology and show that wild pig movement is a better predictor of the optimal response area than the number of ASFv cases early in the outbreak trajectory. Furthermore, our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Aero-assisted orbital plane change using an elliptic drag polar

A three-impulse, aero-assisted maneuver is used to change the plane of a circular orbit. The guidance law used during the atmospheric phase is based on the repetitive use of an approximate optimal control law. The approximations include Loh's term being constant, an exponential atmosphere, and a constant-coefficient drag polar. Whereas the true optimal trajectory is flown at maximum lift-to-drag ratio, simulation results for a parabolic drag polar show the angle of attack becoming large near the end of the trajectory. Here, the approximate optimal control rule is developed for an elliptic polar which has maximum lift coefficient and higher values of the drag coefficient at high values of the lift coefficient than the parabolic polar. Simulation results show that the angle of attack still increases to high values near the end of the trajectory and that, overall, the parabolic drag polar produces better results. Finally, it is shown that Loh's term is not constant over the ascent portion of the atmospheric turn and is the probable cause of high angles of attack. However, the guidance laws developed by assuming Loh's term to be constant work well.

Hull, D. G.↗
NASA NTRS2005

Small Body GN&C Research Report: A Guidance and Control Technique for Small-Body Proximity Operations with Guaranteed Guidance Resolvability and Required Thruster Silent Time

The guidance and control (G&C) algorithms for enabling small-body proximity operations are developed by using a model predictive control approach along with a convexification of the governing dynamics, control constraints, and trajectory/state constraints. The open-loop guidance is solved ahead of time or in a resolvable, real-time manner through the use of PWG (Pseudo Way-point Generation), a technique developed in this research. The PWG scheme ensures required thruster silent times during trajectory maneuvers. The feedback control is implemented to track the PWG trajectories in a manner that guarantees the resolvability for the open-loop problem, enabling the ability to update the G&C in a model-predictive manner. The schemes incorporate gravity models and thruster ring times into discrete dynamics that are solved as a optimal control problem to minimize fuel consumption or thruster energy expenditure. The optimal control problem is cast as an LMI (Linear Matrix Inequality) and then solved through Semi-Definite Programming techniques in a computationally efficient manner that provides convergence and constraint guarantees.

guidance and control (G&C)↗
NASA NTRS1991

Hybrid state-space self-tuning control using dual-rate sampling

This paper presents a hybrid state-space self-tuning control scheme using dual-rate sampling for suboptimal digital adaptive control of linear time-invariant continuous-time multivariable stochastic systems with unknown parameters. An equivalent fast-rate discrete-time state-space innovation model (with estimated states) of the continuous-time system is constructed by using the estimated system parameters and Kalman gain. To utilize the existing optimal regional-pole assignment method developed in the continuous-time domain, the constructed fast-rate discrete-time model is converted into an equivalent continuous-time model for the development of a state-feedback optimal control law with pole placement in a specific region. The developed analog optimal control law is then converted into an equivalent pseudo-slow-rate digital control law via the proposed digital redesign technique, which can be realized via slow-rate digital electronics. The proposed method enables the development of a digitally implementable advanced control algorithm for digital adaptive control of continuous-time multivariable stochastic systems which may be unstable and/or have nonminimum phase.

Shieh, Leang S.↗
DOE OSTI2024

Implementation and validation of optimal start control strategy for air conditioners and heat pumps

Commercial buildings are responsible for approximately 20 % of the total energy consumption and greenhouse gas emissions in the United States. Over 85 % of these buildings lack building automation systems, and many are small (<50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, several operational deficiencies lead to excess energy consumption. Studies have shown that managing the RTUs’ heating and cooling set points, schedules, setbacks, and optimal start can result in a 20 % to 25 % reduction in electricity consumption in small commercial buildings. These buildings typically use fixed schedules to start the RTUs 60 to 120 min before occupancy begins, which results in excess energy consumption. This paper presents research that demonstrates and evaluates the performance of four optimal start methods, which utilize data-based modeling as a key element in facilitating adaptive control in response to time-varying inputs while requiring minimal sensor inputs. The evaluation found energy savings in two commercial buildings equipped with RTUs by periodically alternating four different optimal start models during the cooling and heating season. The resulting energy savings are positive for all models and range from 2 to 5 kWh/day/unit. The units on the east side of the building showed higher savings, while interior units showed greater variability in savings due to the differences in capacities and room sizes. Savings were considerably greater during the heating season compared to the cooling season. The performance of all four models on Mondays was poor; models suggested a shorter optimal start time, which resulted in relatively larger errors. Finally, the future work will look at using a different model for the days after weekends and holidays.

42 ENGINEERING↗