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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Planetary exploration through year 2000, a core program: Mission operations

In 1980 the NASA Advisory Council created the Solar System Exploratory Committee (SSEC) to formulate a long-range program of planetary missions that was consistent with likely fiscal constraints on total program cost. The SSEC had as its primary goal the establishment of a scientifically valid, affordable program that would preserve the nation's leading role in solar system exploration, capitalize on two decades of investment, and be consistent with the coordinated set of scientific stategies developed earlier by the Committe on Planetary and Lunar Exploration (COMPLEX). The result of the SSEC effort was the design of a Core Program of planetary missions to be launched by the year 2000, together with a realistic and responsible funding plan. The Core Program Missions, subcommittee activities, science issues, transition period assumptions, and recommendations are discussed.

Source record↗
DOE OSTI2022

Stochastic Strategic Participation of Active Distribution Networks With High-Penetration DERs in Wholesale Electricity Markets

With the increasing penetration of distributed energy resources (DERs), traditional distribution networks as load-serving entities in wholesale electricity markets, now evolve towards active distribution networks (ADNs) which can proactively participate in wholesale markets by optimally controlling the DERs in their networks. A stochastic bilevel optimization model is proposed in this paper for the strategic participation of ADNs and DERs to provide energy and grid services in wholesale electricity markets. The bilevel optimization model can capture the interactions between the ADN and the wholesale energy and ancillary service markets, considering the uncertainties of DERs in the ADN. In the upper-level model, the ADN makes optimal decisions on energy and reserve bidding considering the availability, uncertainties, and flexibility of DERs. The joint energy and reserve market-clearing of the independent system operator (ISO) is modeled as the lower-level problem. Using strong duality theory and Karush-Kuhn Tucker (KKT) conditions, the proposed bilevel optimization problem is reformulated as mathematical programming with equilibrium constraints (MPEC) problem and further converted into a computationally-solvable mixed-integer second-order-cone programming (MISOCP) model. The simulation results demonstrate the effectiveness of the model and the interactions between an ADN and wholesale electricity markets.

active distribution network↗
DOE OSTI2016

Trading strategies for distribution company with stochastic distributed energy resources

This paper proposes a methodology to address the trading strategies of a proactive distribution company (PDISCO) engaged in the transmission-level (TL) markets. A one-leader multi-follower bilevel model is presented to formulate the gaming framework between the PDISCO and markets. The lower-level (LL) problems include the TL day-ahead market and scenario-based real-time markets, respectively with the objectives of maximizing social welfare and minimizing operation cost. The upper-level (UL) problem is to maximize the PDISCO’s profit across these markets. The PDISCO’s strategic offers/bids interactively influence the outcomes of each market. Since the LL problems are linear and convex, while the UL problem is non-linear and non-convex, an equivalent primal–dual approach is used to reformulate this bilevel model to a solvable mathematical program with equilibrium constraints (MPEC). The effectiveness of the proposed model is verified by case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

A memory-distributed quasi-Newton solver for nonlinear programming problems with a small number of general constraints

We approach the problem of parallelizing state-of-the-art nonlinear programming optimization algorithms.Specifically, we focus on parallelizing quasi-Newton interior-point methods that use limited-memory secant Hessian approximations. Such interior-point methods are known to have better convergence properties and to be more effective on large-scale problems than gradient-based and derivative-free optimization algorithms. We target nonlinear and potentially nonconvex optimization problems with an arbitrary number of bound constraints and a small number of general equality and inequality constraints on the optimization variables. These problems occur for example in the form of optimal control, optimal design, and inverse problems governed by ordinary or partial differential equations, whenever they are expressed in a “reduced-space” optimization approach. We introduce and analyze the time and space complexity of a decomposition method for solving the quasi-Newton linear systems that leverages the fact that the quasi-Newton Hessian matrix has a small number of dense blocks that border a low-rank update of a diagonal matrix. This enables an efficient parallelization on memory-distributed computers of the iterations of the optimization algorithm, a state-of-the-art filter line-search interior-point algorithm by Wächter et. al. We illustrate the efficiency of the proposed method by solving structural topology optimization problems on up to 4608 cores on a parallel machine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Modeling design and control problems involving neural network surrogates

Here, we consider nonlinear optimization problems that involve surrogate models represented by neural networks. We demonstrate first how to directly embed neural network evaluation into optimization models, highlight a difficulty with this approach that can prevent convergence, and then characterize stationarity of such models. We then present two alternative formulations of these problems in the specific case of feedforward neural networks with ReLU activation: as a mixed-integer optimization problem and as a mathematical program with complementarity constraints. For the latter formulation we prove that stationarity at a point for this problem corresponds to stationarity of the embedded formulation. Each of these formulations may be solved with state-of-the-art optimization methods, and we show how to obtain good initial feasible solutions for these methods. We compare our formulations on three practical applications arising in the design and control of combustion engines, in the generation of adversarial attacks on classifier networks, and in the determination of optimal flows in an oil well network.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Final Scientific / Technical Report: Enabling Technologies for Heavy-Duty Vehicles – Cummins 55BTE

The Cummins 55% BTE (55BTE) program has completed the planned technical work on the project. This work includes the planned engine system demonstration in pursuit of the goal of demonstrating a peak system brake thermal efficiency (BTE) of 55%. The engine system included a high efficiency diesel engine integrated with a state-of-the-art waste heat recovery (WHR) system and an advanced aftertreatment system capable of meeting the current emissions standards. While the ultimate program goal of 55% BTE was not fully achieved due to hardware issues during the final testing phase, the program demonstrated a significant increase in reported engine system BTE for a heavy duty sized engine. The previous demonstrations in the Department of Energy funded SuperTruck 1 programs ranged between 50% - 51% BTE. The Cummins 55% BTE program demonstrated 54% BTE. Additionally, the program established a revised path-to-target showing how the system could be improved to reach the ultimate program goal of 55% BTE with some minor modification to the engine system. The changes in the revised path-to-target were unable to be completed during the course of this program due to time and money constraints placed on the program. The program’s goals were challenging in both scope and timing. Although the program’s goal can be simply stated in terms of demonstrating a system efficiency of 55%, the achievement of a heavy-duty diesel engine capable of full torque curve operation, adequate transient performance, low emissions and high brake thermal efficiency (>51% BTE) had not been previously demonstrated in a heavy-duty engine. The closest efforts to date included the SuperTruck 1 programs referenced earlier. The program made several advancements in all system areas. The combustion system was re-designed for a shorter combustion duration and lower in-cylinder heat loss. This was achieved through optimization of the fuel injection rate shape, number of spray holes, piston bowl shape, compression ratio, piston oil cooling, heat flow through the piston and in-cylinder charge motion. The air handling system was re-designed to provide cooled EGR at virtually no pumping penalty. This was achieved through implementation of a dual loop EGR system, reduction of EGR system pressure drop, and implementation of advanced turbocharger efficiency technologies. The engine friction and parasitic signature was dramatically reduced by the program through adoption of variable flow pumps, advanced rings and coatings, rollerized valvetrain, adoption of low viscosity lubricants and reduction in cylinder line bore distortion. The aftertreatment system was optimized through use of low dP substrates and an ammonia gas injection system. The WHR system development included the use of a dual-entry turbine and a mixed charger cooler. Finding and implementing these solutions in a short two-year program at the budgeted funding provided the greatest challenge for the program.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Modeling the Strategic Behavior of an Active Distribution Network in the ISO Markets

With increasing integration of distributed energy resources (DERs), active distribution networks (ADNs) can actively participate in the electricity markets by dispatching their DERs, which can change the existing electricity market paradigm. It is essential to investigate the strategic behaviors of ADNs and their DER dispatch when they participate in the wholesale market as price-makers. This paper proposes a bi-level optimization model to study the strategic behavior of an ADN in both energy and reserve markets. The optimal scheduling of DERs in the ADN is modeled as the upper level problem and the joint energy and reserve market-clearing of the ISO is modeled as the lower-level problem. The two-level optimization models exchange bidding information and energy/reserve prices with each other. The proposed bi-Ievel optimization problem is converted to a mathematical programming with equilibrium constraints (MPEC) by using Karush-Kuhn Tucker (KKT) conditions and strong duality theory. Further, the MPEC problem is reformulated as a computationally-solvable mixed integer second order cone programming (MISOCP) model. The simulation results on an illustrative case demonstrate the impact of the strategic bidding of the ADN on the day-ahead energy and reserve market prices.

active distribution network↗
NASA NTRS1998

Strategies and Recommended Targets for Mars Surveyor Program Landing Sites

The two major constraints for selecting the Mars Surveyor Program (MSP) 2001 landing site at the time of this meeting are latitude (30'N to 15S) and elevation (< 2.5 km). The latitude belt will be narrowed down to a 15' sector after this workshop. This mission will demonstrate the capability to perform a precision landing, with the goal of achieving an accuracy of approximately 10 km, 3-sigma. There will be at least two different landing sites ('01 and '03) selected in the MSP. However, there should be an option of having the '05 sample return mission land in a different site and the '05 mission should be equipped with a rover for two reasons. The reasoning behind this follows: '05 lander/rover package should have the option of going to an independent site from either '01 or '03 because predecessor missions (orbital) may locate the "Ultimate Site"; '05 needs a rover to either: (A) explore and sample this "ultimate site" for sample return; (B) retrieve samples from '01 or '03 rovers, as a contingency, in case these rovers malfunction and cannot negotiate the trek back to the sample return vehicle.

Rice, James W., Jr.↗
DOE OSTI2018

Strategic Offering for Wind Power Producers Considering Energy and Flexible Ramping Products

The increasing deployments of renewable generation methods, such as wind, affects the flexibility of electric power system operating due to their inherent variability and uncertainty. To mitigate this, power systems need flexible resources. This paper investigates the potential for wind power to provide flexible ramping products in the real-time market, an additional value stream to the energy it provides. The proposed model for wind power’s strategic offering is formulated as a bi-level optimization problem with wind profit maximization at the upper level and the independent system operator’s economic dispatch—considering both the energy balance and the flexible ramping requirement to counter uncertainty—at the lower level. This bi-level model is converted to a mathematical program with equilibrium constraints (MPEC) by recasting the lower level problem with its Karush–Kuhn–Tucker optimality conditions. Then, through strong duality theory and the big-M method, the MPEC model is converted to a mixed-integer linear programming model. The opportunity cost and the price for wind power-providing ramping products are analyzed. Numerical examples based on a 5-bus network are presented to verify the proposed model and concept.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Path-Adaptive Guidance Algorithm Trades for a Two-Stage Lunar Descent Vehicle

For the next generation of NASA’s missions, explicit, path-adaptive descent guidance algorithms must provide the stability and customizability required for a safe and efficient descent to the lunar surface, while also meeting program and vehicle constraints. Several descent algorithms have been flown and tested for single-stage landers through the Apollo and Altair programs, but thus far little analysis has been conducted involving the application of these algorithms to a two-stage descent vehicle. Due to payload mass and fairing constraints of the existing fleet of launch vehicles, multi-stage descent architectures are a unique option for achieving the greatest possible mass to lunar surface. This paper seeks to compare the performance of guidance configurations of a lunar lander system consisting of two stages, one of which separates partway through descent. Through development of this paper, an optimization suite has been written that is specifically designed for optimizing planetary non-atmospheric two-stage descent trajectories, and is used as a baseline to compare the guidance algorithms tested. Time-to-go computational methods and ignition logic routines that may be employed in a lunar environment are also discussed. Preliminary results are presented that show relative performance metrics for a range of different guidance algorithm configurations.

Jason M Everett↗
NASA NTRS2020

Path-Adaptive Guidance Algorithm Trades for a Two-Stage Lunar Descent Vehicle

For the next generation of NASA’s missions, the necessity for path-adaptive guidance algorithms has become clear in order to provide the stability and customizability required for a safe and efficient descent to the lunar surface, while meeting specified program and vehicle constraints. Several descent algorithms have been tested and flown for single-stage landers through the Apollo and Altair programs, but thus far little analysis has been conducted involving the application of these algorithms for a two-stage descent vehicle. Due to the limited payload mass constraints of the existing fleet of launch vehicles, multi-stage descent architectures have become a viable course of action. This paper seeks to compare the performance of guidance configurations for a lunar lander system consisting of two stages, one of which separates partway through descent. Through development of this paper, an optimization suite has been written that is specifically designed for optimizing planetary non-atmospheric two-stage descent trajectories, and is used as a comparison baseline for the guidance algorithms tested. Time-to -go computational methods and ignition logic routines that may be employed in a lunar environment are also discussed. Further work is to be completed on trajectory design trades as well as the effects of modifying guidance targets in simulation based on trajectories that are optimized for different performance indices.

Jason M Everett↗
NASA NTRS1996

A System for Automatically Generating Scheduling Heuristics

The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.

Morris, Robert↗
NASA NTRS2005

Quadratic Programming for Allocating Control Effort

A computer program calculates an optimal allocation of control effort in a system that includes redundant control actuators. The program implements an iterative (but otherwise single-stage) algorithm of the quadratic-programming type. In general, in the quadratic-programming problem, one seeks the values of a set of variables that minimize a quadratic cost function, subject to a set of linear equality and inequality constraints. In this program, the cost function combines control effort (typically quantified in terms of energy or fuel consumed) and control residuals (differences between commanded and sensed values of variables to be controlled). In comparison with prior control-allocation software, this program offers approximately equal accuracy but much greater computational efficiency. In addition, this program offers flexibility, robustness to actuation failures, and a capability for selective enforcement of control requirements. The computational efficiency of this program makes it suitable for such complex, real-time applications as controlling redundant aircraft actuators or redundant spacecraft thrusters. The program is written in the C language for execution in a UNIX operating system.

Singh, Gurkirpal↗
DOE OSTI2018

Preliminary cosmological constraints from the Dark Energy Survey Supernova Program using the 3 year Spectroscopic Sample

The Dark Energy Survey (DES) is using four probes to investigate the dynamics of the expansion of the Universe. The DES Supernova Program (DES-SN) is observing 27 square degrees with a 6-day cadence to obtain a large sample of type Ia supernovae for cosmology. In collaboration with DES, the Australian Dark Energy Survey (OzDES) is using the AAT to obtain redshifts and classications for objects in the DES elds. While probing dark energy using type Ia supernovae is the primary aim of the supernova survey, the observing strategy enables us to conduct a number of other investigations, such as AGN reverberation mapping and galactic evolution studies. We present preliminary cosmological constraints from the rst 3-years of the DES-SN survey. The sample contains 206 spectroscopically conrmed Type Ia Supernovae (0:02 < z < 0:9) discovered during the rst 3 years of the DES-SN. The photometric calibration, scene modeling photometric pipeline, additional low-z supernovae samples (z < 0:1), as well as the cosmological results and systematics analysis are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Modeling the Strategic Behavior of an Active Distribution Network in the ISO Markets

With increasing integration of distributed energy resources (DERs), active distribution networks (ADNs) can actively participate in the electricity markets by dispatching their DERs, which can change the existing electricity market paradigm. It is essential to investigate the strategic behaviors of ADNs and their DER dispatch when they participate in the wholesale market as price-makers. This paper proposes a bi-level optimization model to study the strategic behavior of an ADN in both energy and reserve markets. The optimal scheduling of DERs in the ADN is modeled as the upper level problem and the joint energy and reserve market-clearing of the ISO is modeled as the lower-level problem. The two-level optimization models exchange bidding information and energy/reserve prices with each other. The proposed bi-Ievel optimization problem is converted to a mathematical programming with equilibrium constraints (MPEC) by using Karush-Kuhn Tucker (KKT) conditions and strong duality theory. Further, the MPEC problem is reformulated as a computationally-solvable mixed integer second order cone programming (MISOCP) model. The simulation results on an illustrative case demonstrate the impact of the strategic bidding of the ADN on the day-ahead energy and reserve market prices.

Xue, Yaosuo↗
NASA NTRS1987

Motion coordination and programmable teleoperation between two industrial robots

Tasks for two coordinated industrial robots always bring the robots in contact with a same object. The motion coordination among the robots and the object must be maintained all the time. To plan the coordinated tasks, only one robot's motion is planned according to the required motion of the object. The motion of the second robot is to follow the first one as specified by a set of holonomic equality constraints at every time instant. If any modification of the object's motion is needed in real-time, only the first robot's motion has to be modified accordingly in real-time. The modification for the second robot is done implicitly through the constraint conditions. Thus the operation is simplified. If the object is physically removed, the second robot still continually follows the first one through the constraint conditions. If the first robot is maneuvered through either the teach pendant or the keyboard, the second one moves accordingly to form the teleoperation which is linked through the software programming. Obviously, the second robot does not need to duplicate the first robot's motion. The programming of the constraints specifies their relative motions.

Luh, J. Y. S.↗