A closed-loop, approximately time-optimal control method for linear systems.
Eigenvector scalar product solutions for closed loop time optimal control of linear systems
LINEAR SYSTEM↗
SEARCH · Engineering Papers
Results for “system optimization”
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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Utilizing waste heat in wastewater treatment plants for water desalination: Modeling and Multi-Objective optimization of a Multi-Effect desalination system using Decision Tree Regression and Pelican optimization algorithm
This paper examines the feasibility of using waste heat from wastewater treatment plants (WWTPs) for water desalination. A model was developed to utilize waste heat from the gensets at As Samra WWTP in Jordan, using real data and TRNSYS® software to calculate available waste heat. The desalination process was then modeled with ASPEN PLUS® software, focusing on multi-effect desalination (MED). Both series and parallel configurations for the MED system were compared. The study investigated the effects of system feeding flow rate, feeding pressure, and heat input on productivity, performance ratio, and recovery ratio. The study also introduces a novel optimization technique combining machine learning and modern optimization algorithms to maximize system productivity and performance. Initially, a decision tree regression (DTR) model is developed to establish relationships between key independent variables (flow rate, feed pressure, and heat input) and dependent variables (productivity, performance ratio, and recovery ratio). The Pelican Optimization Algorithm (POA) is then used to identify the optimal values of the independent variables for maximum productivity and performance. The results show that using a series configuration yields a system productivity of 3984.2 kg/hr, a performance ratio of 3.78, and a recovery ratio of 0.991 at a feed flow rate of 4000 kg/hr, feed pressure of 3 bars, and heat input of 719 kW. Optimal productivity (4421 kg/hr), performance ratio (3.81), and recovery ratio (0.851) are achieved at a feed flow rate of 5166 kg/hr, feed pressure of 3.2 bars, and heat input of 794 kW. In conclusion, the techno-economic assessment indicates a levelized cost of water of 1.63 USD/m 3 for parallel configurations and 1.65 USD/m 3 for series configurations, with a payback period of less than two years.
42 ENGINEERING↗
Optimal output-feedback controllers for linear systems
Matrix method for optimal feedback control of linear systems
Levine, W. S.↗
Nano-enhanced solid-state hydrogen storage: Balancing discovery and pragmatism for future energy solutions
Nanomaterials have revolutionized the battery industry by enhancing energy storage capacities and charging speeds, and their application in hydrogen (H 2 ) storage likewise holds strong potential, though with distinct challenges and mechanisms. H 2 is a crucial future zero-carbon energy vector given its high gravimetric energy density, which far exceeds that of liquid hydrocarbons. However, its low volumetric energy density in gaseous form currently requires storage under high pressure or at low temperature. This review critically examines the current and prospective landscapes of solid-state H 2 storage technologies, with a focus on pragmatic integration of advanced materials such as metal-organic frameworks (MOFs), magnesium-based hybrids, and novel sorbents into future energy networks. These materials, enhanced by nanotechnology, could significantly improve the efficiency and capacity of H 2 storage systems by optimizing H 2 adsorption at the nanoscale and improving the kinetics of H 2 uptake and release. We discuss various H 2 storage mechanisms—physisorption, chemisorption, and the Kubas interaction—analyzing their impact on the energy efficiency and scalability of storage solutions. The review also addresses the potential of “smart MOFs”, single-atom catalyst-doped metal hydrides, MXenes and entropy-driven alloys to enhance the performance and broaden the application range of H 2 storage systems, stressing the need for innovative materials and system integration to satisfy future energy demands. High-throughput screening, combined with machine learning algorithms, is noted as a promising approach to identify patterns and predict the behavior of novel materials under various conditions, significantly reducing the time and cost associated with experimental trials. In closing, we discuss the increasing involvement of various companies in solid-state H 2 storage, particularly in prototype vehicles, from a techno-economic perspective. In conclusion, this forward-looking perspective underscores the necessity for ongoing material innovation and system optimization to meet the stringent energy demands and ambitious sustainability targets increasingly in demand.
25 ENERGY STORAGE↗
System design study for an optimal remote oculometer for use in operational aircraft
System design of optimal remote oculometer for use in operational aircraft
Mason, K. A.↗
Optimization of space manufacturing systems
Four separate analyses are detailed: transportation to low earth orbit, orbit-to-orbit optimization, parametric analysis of SPS logistics based on earth and lunar source locations, and an overall program option optimization implemented with linear programming. It is found that smaller vehicles are favored for earth launch, with the current Space Shuttle being right at optimum payload size. Fully reusable launch vehicles represent a savings of 50% over the Space Shuttle; increased reliability with less maintenance could further double the savings. An optimization of orbit-to-orbit propulsion systems using lunar oxygen for propellants shows that ion propulsion is preferable by a 3:1 cost margin over a mass driver reaction engine at optimum values; however, ion engines cannot yet operate in the lower exhaust velocity range where the optimum lies, and total program costs between the two systems are ambiguous. Heavier payloads favor the use of a MDRE. A parametric model of a space manufacturing facility is proposed, and used to analyze recurring costs, total costs, and net present value discounted cash flows. Parameters studied include productivity, effects of discounting, materials source tradeoffs, economic viability of closed-cycle habitats, and effects of varying degrees of nonterrestrial SPS materials needed from earth. Finally, candidate optimal scenarios are chosen, and implemented in a linear program with external constraints in order to arrive at an optimum blend of SPS production strategies in order to maximize returns.
Akin, D. L.↗
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow
This paper examines the problem of real-time optimization of networked systems and develops online algorithms that steer the system towards the optimal trajectory without explicit knowledge of the system model. The problem is modeled as a dynamic optimization problem with time-varying performance objectives and engineering constraints. The design of the algorithms leverages the online zero-order primal-dual projected-gradient method. In particular, the primal step that involves the gradient of the objective function (and hence requires a networked systems model) is replaced by its zero-order approximation with two function evaluations using a deterministic perturbation signal. The evaluations are performed using the measurements of the system output, hence giving rise to a feedback interconnection, with the optimization algorithm serving as a feedback controller. The paper provides some insights on the stability and tracking properties of this interconnection. Finally, the paper applies this methodology to a real-time optimal power flow problem in power systems, and shows its efficacy on the IEEE 37-node distribution test feeder for reference power tracking and voltage regulation.
61 RADIATION PROTECTION AND DOSIMETRY↗
Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)
Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.
Kasahara, Hironori↗
Optimization of the propulsion cycles for advanced shuttles. I - Propulsion mass model methodology
During the past year NASA and DLR computer codes were combined in order to analyze and optimize advanced rocket launcher systems. Previous optimization results led to relatively low chamber pressures and nozzle area ratios for the different cycles. Additional effort has been made to improve the verification of propulsive parameters such as chamber pressure, nozzle extension, kind of cycle, tripropellant systems, variable mixture ratio rocket motors, new technology effects, etc. The emphasis of this paper is to describe the methodology of the improved propulsion mass model.
Manski, Detlef↗
Large scale optimization using ASTROS: An overview
Interest in interdisciplinary systems is widespread around the world. A number of structural optimization systems are being developed and tested. Some examples are listed here. ASOP, FASTOP, and TSO are programs developed for the Air Force Flight Dynamics Laboratory during the seventies. These programs established the feasibility of integrating various disciplines. The program 'STARS' is basically a structural optimization system developed by the Royal Aircraft Establishment (RAE) in England. At present, it is being enhanced to include aeroelasticity. 'LAGRANGE' is an optimization system developed by MBB in Germany. ELFINI is a similar system developed in France. It is being marketed in the U.S. as well as other countries. The Automated STRuctural Optimization System (ASTROS) was developed for the Flight Dynamics Directorate of Wright Laboratory. The ASTROS system is described in viewgraph form.
Venkayya, Vipperia B.↗
A Descriptive Model for Determining Optimal Human Performance in Systems, Volume 1
Man machine development cycle and mathematical models for optimal human performance
Source record↗
l1-optimal control of multivariable systems with output norm constraints
This paper considers the l1-optimal control problem for general rational plants. It is shown that, for plants with no poles or zeros on the unit circle, an optimal compensator exists and that the resulting closed loop transfer function is polynomial whenever there are at least as many controls as regulated outputs and at least as many measurements as exogeneous inputs. Exactly or approximately, optimal rational compensators can be obtained by solving a sequence of finite linear programs for the coefficients of a polynomial closed-loop transfer function. No assumptions on plant poles or zeros are required to obtain at least approximately optimal compensators. It is shown that constrained problems in which a set of outputs is regulated subject to l(infinity)-norm constraints on another set of outputs can be solved using a slight modification of the same algorithm.
Mcdonald, J. S.↗
Hamiltonian Optimal Control of Distributed Lagrangian Systems
This lecture presents a Hamiltonian control method and a distributed optimal control method for distributed Lagrangian systems. The distributed optimal control theory is formulated using a semi-group abstraction resulting in an integro-differential Riccati equation.
Distributed Optimal Control↗
A system approach to aircraft optimization
Mutual couplings among the mathematical models of physical phenomena and parts of a system such as an aircraft complicate the design process because each contemplated design change may have a far reaching consequence throughout the system. Techniques are outlined for computing these influences as system design derivatives useful for both judgemental and formal optimization purposes. The techniques facilitate decomposition of the design process into smaller, more manageable tasks and they form a methodology that can easily fit into existing engineering organizations and incorporate their design tools.
Sobieszczanski-Sobieski, Jaroslaw↗
A system approach to aircraft optimization
Mutual couplings among the mathematical models of physical phenomenon and parts of a system such as an aircraft complicate the design process because each contemplated design change may have far reaching consequences throughout the system. This paper outlines techniques for computing these influences as system design derivatives useful in both judgmental and formal optimization purposes. The techniques facilitate decomposition of the design process into smaller, more manageable tasks and they form a methodology that can easily fit into existing engineering optimizations and incorporate their design tools.
Sobieszczanski-Sobieski, Jaroslaw↗
Carbides in iron-rich Fe-Mn-Cr-Mo-Al-Si-C systems
The optimization of high carbon iron-base superalloy properties with duplex microstructure gamma + M7C3 carbide requires analysis in the context of a seven-component system. Data are first provided here for the Fe-Mn-Cr-Mo-C quinary system, at 30 at. pct carbon. A characterization of competing carbides, according to a pseudoternary phase diagram at 35 wt pct iron, is made from isothermal sections. It is noted that while M7C3 and M3C carbides' occurrences are respectively favored at the Cr and Mn corners, the M2C carbide and molybdenum cementite are predominant with increasing amounts of Mo. Lattice parameters are reported for the various carbides.
Lemkey, F. D.↗
Small Spacecraft System-Level Design and Optimization for Interplanetary Trajectories
The feasibility of an interplanetary mission for a CubeSat, a type of miniaturized spacecraft, that uses an emerging technology, the CubeSat Ambipolar Thruster (CAT) is investigated. CAT is a large delta-V propulsion system that uses a high-density plasma source that has been miniaturized for small spacecraft applications. An initial feasibility assessment that demonstrated escaping Low Earth Orbit (LEO) and achieving Earth-escape trajectories with a 3U CubeSat and this thruster technology was demonstrated in previous work. We examine a mission architecture with a trajectory that begins in Earth orbits such as LEO and Geostationary Earth Orbit (GEO) which escapes Earth orbit and travels to Mars, Jupiter, or Saturn. The goal was to minimize travel time to reach the destinations and considering trade-offs between spacecraft dry mass, fuel mass, and solar power array size. Sensitivities to spacecraft dry mass and available power are considered. CubeSats are extremely size, mass, and power constrained, and their subsystems are tightly coupled, limiting their performance potential. System-level modeling, simulation, and optimization approaches are necessary to find feasible and optimal operational solutions to ensure system-level interactions are modeled. Thus, propulsion, power/energy, attitude, and orbit transfer models are integrated to enable systems-level analysis and trades. The CAT technology broadens the possible missions achievable with small satellites. In particular, this technology enables more sophisticated maneuvers by small spacecraft such as polar orbit insertion from an equatorial orbit, LEO to GEO transfers, Earth-escape trajectories, and transfers to other interplanetary bodies. This work lays the groundwork for upcoming CubeSat launch opportunities and supports future development of interplanetary and constellation CubeSat and small satellite mission concepts.
Spangelo, Sara↗
Model-Free Primal-Dual Methods for Network Optimization with Application to Real-Time Optimal Power Flow: Preprint
This paper examines the problem of real-time optimization of networked systems and develops online algorithms that steer the system towards the optimal trajectory without explicit knowledge of the system model. The problem is modeled as a dynamic optimization problem with time-varying performance objectives and engineering constraints. The design of the algorithms leverages the online zero-order primal-dual projected-gradient method. In particular, the primal step that involves the gradient of the objective function (and hence requires networked systems model) is replaced by its zero-order approximation with two function evaluations using a deterministic perturbation signal. The evaluations are performed using the measurements of the system output, hence giving rise to a feedback interconnection, with the optimization algorithm serving as a feedback controller. The paper provides some insights on the stability and tracking properties of this interconnection. Finally, the paper applies this methodology to a real-time optimal power flow problem in power systems, and shows its efficacy on the IEEE 37-node distribution test feeder for reference power tracking and voltage regulation.
61 RADIATION PROTECTION AND DOSIMETRY↗