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Results for “automated 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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At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRS1986

Optical system design, analysis, and production for advanced technology systems; Proceedings of the Meeting, Innsbruck, Austria, Apr. 15-17, 1986

The present conference considers topics in the fields of optical systems design software, the design and analysis of optical systems, illustrative cases of advanced optical system design, the integration of optical designs into greater systems, and optical fabrication and testing techniques. Attention is given to an extended range diffraction-based merit function for lens design optimization, an assessment of technologies for stray light control and evaluation, the automated characterization of IR systems' spatial resolution, a spectrum of design techniques based on aberration theory, a three-field IR telescope, a large aperture zoom lens for 16-mm motion picture cameras, and the use of concave holographic gratings as monochomators. Also discussed are the use of aspherics in optical systems, glass choice procedures for periscope design, the fabrication and testing of unconventional optics, low mass mirrors for large optics, and the diamond grinding of optical surfaces on aspheric lens molds.

Fischer, Robert E.↗

DOE OSTI2023

Automated Adversary-in-the-Loop Cyber-Physical Defense Planning

Security of cyber-physical systems (CPS) continues to pose new challenges due to the tight integration and operational complexity of the cyber and physical components. To address these challenges, this article presents a domain-aware, optimization-based approach to determine an effective defense strategy for CPS in an automated fashion—by emulating a strategic adversary in the loop that exploits system vulnerabilities, interconnection of the CPS, and the dynamics of the physical components. Our approach builds on an adversarial decision-making model based on a Markov Decision Process (MDP) that determines the optimal cyber (discrete) and physical (continuous) attack actions over a CPS attack graph. The defense planning problem is modeled as a non-zero-sum game between the adversary and defender. We use a model-free reinforcement learning method to solve the adversary’s problem as a function of the defense strategy. We then employ Bayesian optimization (BO) to find an approximate best-response for the defender to harden the network against the resulting adversary policy. This process is iterated multiple times to improve the strategy for both players. We demonstrate the effectiveness of our approach on a ransomware-inspired graph with a smart building system as the physical process. Numerical studies show that our method converges to a Nash equilibrium for various defender-specific costs of network hardening.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1998

Bioregenerative life support: not a picnic

If humans are to live permanently in space, regenerative life support systems are an enabling technology and must replace the picnic approach of taking all supplies required for each mission. These systems are classified by technologies as either physical/chemical or bioregenerative. Both of these system-types can recycle water, remove carbon dioxide, produce oxygen, and recover essential elements from waste products. Bioregenerative can also produce food, thus, making it essential if humans are to exist in space independent of earth. A solely bioregenerative life support system includes plants as a biomass production module and microbial organisms in bioreactors as a resource recovery module. In the Advanced Life Support Program, bioregenerative life support systems are being investigated through a research and technology development project which includes large scale testing as part of the Breadboard Project and human tests conducted in the soon to be constructed BioPlex facility. Research and technology development efforts are directed toward optimizing biomass productivity in controlled chambers by developing light weight, energy efficient, and automated systems; recycling liquid and solid wastes; baselining the operation of bioreactors; determining system microbial stability; assessing chemical contamination; and building models required for long term system operations. The program will include space flight studies in the near future to determine if these life support technologies will function in microgravity. When a bioregenerative system is finally incorporated into a mission, the conversion from a picnic and resupply mentality to permanent recycling and independence from earth will be complete.

NASA Center KSC↗

NASA NTRS2011

Capacitance Based Moisture Sensing for Microgravity Plant Modules: Sensor Design and Considerations

Life support systems for growing plants in microgravity should strive for providing optimal growing conditions and increased automation. Accurately tracking soil moisture content can forward both of these aims, so an attempt was made to instrument a microgravity growth module currently in development, the VEGGIE rooting pillow, in order to monitor moisture levels. Two electrode systems for a capacitance-based moisture sensor were tested. Trials with both types of electrodes showed a linear correlation between observed capacitance and water content over certain ranges of moisture within the pillows. Overall, both types of the electrodes and the capacitance-based moisture sensor are promising candidates for tracking water levels for microgravity plant growth systems.

Schaber, Chad L.↗

NASA NTRS1978

Duct wall impedance control as an advanced concept for acoustic suppression enhancement

A systems concept procedure is described for the optimization of acoustic duct liner design for both uniform and multisegment types. The concept was implemented by the use of a double reverberant chamber flow duct facility coupled with sophisticated computer control and acoustic analysis systems. The optimization procedure for liner insertion loss was based on the concept of variable liner impedance produced by bias air flow through a multilayer, resonant cavity liner. A multiple microphone technique for in situ wall impedance measurements was used and successfully adapted to produce automated measurements for all liner configurations tested. The complete validation of the systems concept was prevented by the inability to optimize the insertion loss using bias flow induced wall impedance changes. This inability appeared to be a direct function of the presence of a higher order energy carrying modes which were not influenced significantly by the wall impedance changes.

Dean, P. D.↗

NASA NTRS2016

Human-Robot Interaction in High Vulnerability Domains

Future NASA missions will require successful integration of the human with highly complex systems. Highly complex systems are likely to involve humans, automation, and some level of robotic assistance. The complex environments will require successful integration of the human with automation, with robots, and with human-automation-robot teams to accomplish mission critical goals. Many challenges exist for the human performing in these types of operational environments with these kinds of systems. Systems must be designed to optimally integrate various levels of inputs and outputs based on the roles and responsibilities of the human, the automation, and the robots; from direct manual control, shared human-robotic control, or no active human control (i.e. human supervisory control). It is assumed that the human will remain involved at some level. Technologies that vary based on contextual demands and on operator characteristics (workload, situation awareness) will be needed when the human integrates into these systems. Predictive models that estimate the impact of the technologies on the system performance and the on the human operator are also needed to meet the challenges associated with such future complex human-automation-robot systems in extreme environments.

workload↗

NASA NTRS1990

Automated control of hierarchical systems using value-driven methods

An introduction is given to the Value-driven methodology, which has been successfully applied to solve a variety of difficult decision, control, and optimization problems. Many real-world decision processes (e.g., those encountered in scheduling, allocation, and command and control) involve a hierarchy of complex planning considerations. For such problems it is virtually impossible to define a fixed set of rules that will operate satisfactorily over the full range of probable contingencies. Decision Science Applications' value-driven methodology offers a systematic way of automating the intuitive, common-sense approach used by human planners. The inherent responsiveness of value-driven systems to user-controlled priorities makes them particularly suitable for semi-automated applications in which the user must remain in command of the systems operation. Three examples of the practical application of the approach in the automation of hierarchical decision processes are discussed: the TAC Brawler air-to-air combat simulation is a four-level computerized hierarchy; the autonomous underwater vehicle mission planning system is a three-level control system; and the Space Station Freedom electrical power control and scheduling system is designed as a two-level hierarchy. The methodology is compared with rule-based systems and with other more widely-known optimization techniques.

Pugh, George E.↗

DOE OSTI2026

Optimization-based approaches to control of connected and automated vehicles: Principles, complexities, applications, challenges, and outlook

Safe and optimal motion control for connected and automated vehicles (CAVs) poses a fundamental optimization challenge at the intersection of system complexity, environmental uncertainty, and stringent real-time constraints. Existing surveys address this challenge in isolation – focusing either on specific control techniques or individual uncertainty sources – without providing a unified framework that characterizes the trade-offs among computational tractability, performance verifiability, and adaptive generalization across paradigms. This review addresses that gap by presenting a cohesive analytical framework concentrated on the decision-making and trajectory optimization layers of the CAV autonomy stack. We systematically analyze three major optimization paradigms – first-principles model-based optimization, data-driven methods, and hybrid synergistic architectures – evaluating each against four core complexity axes: problem formulation, constraint handling, optimality guarantees, and robustness. Key applications including platooning, trajectory planning, collision avoidance, and cooperative control are examined to reveal recurring methodological patterns and critical operational constraints that limit real-world performance. Our synthesis identifies verifiable hybrid architectures, incentive-aligned multi-agent cooperation, and hardware-algorithm co-design as the defining research frontiers, and distills a targeted agenda for developing CAV control systems that are simultaneously safe, computationally efficient, and deployable in the full complexity of real-world traffic environments.

Muzahid, Abu Jafar Md [University of Tennessee, Kn↗

DOE OSTI2021

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops a machine learning based approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurement. The machine learning model is developed by using random forest algorithm. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

advanced metering infrastructure↗

NASA NTRS2008

Mission Activity Planning for Humans and Robots on the Moon

A series of studies is conducted to develop a systematic approach to optimizing, both in terms of the distribution and scheduling of tasks, scenarios in which astronauts and robots accomplish a group of activities on the Moon, given an objective function (OF) and specific resources and constraints. An automated planning tool is developed as a key element of this optimization system.

task allocation↗

NASA NTRS2018

Numerical Simulation of AFP Nip Point Temperature Prediction for Complex Geometries

Material placement at the ideal nip point temperature over complex surfaces with uniformity across the width of the compaction rollers results in optimized part properties for Automated Fiber Placement (AFP) processes. However, current AFP systems utilize heat control models and methodologies, based on multiple process parameters such as feed-rate and orientation, that are mostly open-loop. Here, infrared (IR) heater input is calibrated as a function of process parameters during machine qualification. This work presents a numerical simulation to predict arrayed-infrared (AIR) emitter radiation onto a substrate that includes view factor implementation, IR radiative heat flow calculation, energy rate balance, and a transient heat transfer model. The purpose of this numerical model is to predict nip point temperature on complex surfaces, serving as a baseline for a new arrayed-infrared (AIR) thermoset heater to improve AFP process control. It is anticipated that this simulation will accurately control the temperature for high-speed AFP layup of complex geometries. An anticipated result of an AIR heater system is that material calibration and testing will be reduced as temperature is instantaneously monitored and controlled. Therefore, temperature across the roller width will be uniform during placement of complex parts, independent of their geometry.

Xia, Kaishu↗

DOE OSTI2021

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops an approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurements. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements: Preprint

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops an approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurements. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1986

An expert system for choosing the best combination of options in a general purpose program for automated design synthesis

An expert system called EXADS has been developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. ADS has approximately 100 combinations of strategy, optimizer, and one-dimensional search options from which to choose. It is difficult for a nonexpert to make this choice. This expert system aids the user in choosing the best combination of options based on the users knowledge of the problem and the expert knowledge stored in the knowledge base. The knowledge base is divided into three categories; constrained problems, unconstrained problems, and constrained problems being treated as unconstrained problems. The inference engine and rules are written in LISP, contains about 200 rules, and executes on DEC-VAX (with Franz-LISP) and IBM PC (with IQ-LISP) computers.

Rogers, J. L.↗

DOE OSTI2025

Architectural Approaches for Integrating ADMS and DERMS: Challenges, Comparisons, and Real-World Use Cases

The electrical distribution landscape is rapidly transforming due to the proliferation of distributed energy resources (DERs) such as solar panels, wind turbines, battery storage systems, combined heat and power units, and electric vehicles, introducing variability and uncontrollability that traditional grid operators are ill-equipped to manage. This transformation is further accelerated by advancements in Information and Communication Technology infrastructure that connects control centers with end devices, demanding automation and a deeper understanding of new technologies by utility personnel. Advanced grid control techniques using system-level optimization, Artificial Intelligence, and Machine Learning at the enterprise level and distributed level are evolving to address these issues. There is also an opportunity to utilize the enormous data created by these new DER technologies in the grid. Advanced Distribution Management Systems (ADMS) and Distributed Energy Resource Management Systems (DERMS) are critical in addressing these challenges by automating grid operations and enhancing reliability. Given the relatively recent development of ADMS and DERMS, and the still relatively low level of ADMS and DERMS deployment in the industry, there is a notable deficiency in the comprehensive understanding of the challenges and benefits associated with these new technologies, especially with their complementary natures and integration architectures. This paper aims to bridge the knowledge gap in ADMS and DERMS integration, presenting three distinct integration architectures currently available, and discussing the challenges and benefits of each architecture to guide utilities, industry professionals, and researchers in optimizing grid management and decision-making processes for a resilient and efficient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1990

Application of heuristic satellite plan synthesis algorithms to requirements of the WARC-88 allotment plan

Creation of an Allotment Plan for the Fixed Satellite Service at the 1988 Space World Administrative Radio Conference (WARC) represented a complex satellite plan synthesis problem, involving a large number of planned and existing systems. Solutions to this problem at WARC-88 required the use of both automated and manual procedures to develop an acceptable set of system positions. Development of an Allotment Plan may also be attempted through solution of an optimization problem, known as the Satellite Location Problem (SLP). Three automated heuristic procedures, developed specifically to solve SLP, are presented. The heuristics are then applied to two specific WARC-88 scenarios. Solutions resulting from the fully automated heuristics are then compared with solutions obtained at WARC-88 through a combination of both automated and manual planning efforts.

Heyward, Ann O.↗

NASA NTRS1990

Application of heuristic satellite plan synthesis algorithms to requirements of the WARC-88 allotment plan

Heyward, Ann O.↗

NASA NTRS1997

BATSE imaging survey of the Galactic plane

The burst and transient source experiment (BATSE) onboard the Compton Gamma Ray Observatory (CGRO) provides all sky monitoring capability, occultation analysis and occultation imaging which enables new and fainter sources to be searched for in relatively crowded fields. The occultation imaging technique is used in combination with an automated BATSE image scanner, allowing an analysis of large data sets of occultation images for detections of candidate sources and for the construction of source catalogs and data bases. This automated image scanner system is being tested on archival data in order to optimize the search and detection thresholds. The image search system, its calibration results and preliminary survey results on archival data are reported on. The aim of the survey is to identify a complete sample of black hole candidates in the galaxy and constrain the number of black hole systems and neutron star systems.

Grindlay, J. E.↗