SEARCH · Engineering Papers

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37

All sources NASA NTRS DOE OSTI

NASA NTRS1994

Advanced support systems development and supporting technologies for Controlled Ecological Life Support Systems (CELSS)

A methyl acetate reactor was developed to perform a subscale kinetic investigation in the design and optimization of a full-scale metabolic simulator for long term testing of life support systems. Other tasks in support of the closed ecological life support system test program included: (1) heating, ventilation and air conditioning analysis of a variable pressure growth chamber, (2) experimental design for statistical analysis of plant crops, (3) resource recovery for closed life support systems, and (4) development of data acquisition software for automating an environmental growth chamber.

Simon, William E.↗

NASA NTRS2001

Efficient Translation of LTL Formulae into Buchi Automata

Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.

Giannakopoulou, Dimitra↗

NASA NTRS1975

Interim Report of the Astronomy Spacelab Payloads Study: Ultraviolet and Optical Astronomy - Volume 2

The Space Shuttle will comprise NASA's primary transportation system into near-earth orbit during the 1980s. The Shuttle will provide the astronomical community with a major new capability to send a wide variety of instrumentation into orbit, to utilize it there under manned or automatic control for periods from seven to thirty days, and to return it to the ground. To this end the European Space Research Organization (ESRO) is developing Spacelab, an array of interchangeable components -pressurized manned modules, unpressurized pallets and related support systems - to be mounted in the Shuttle payload bay. Spacelab will offer important opportunities to carry out astronomical research with instruments optimized for specific objectives. With a high flight frequency and with the ability to modify or interchange telescopes and instruments between flights, one will not need to make rigid long-term commitments to specific and compromised telescope/instrument/ detector combinations as is the case for automated satellites. Observational techniques demanding the physical return of data and equipment - in particular the use of photographic film, instruments requiring tight calibration controls, cryogens, high-risk detectors and degradeable optical coatings -will open research areas not readily addressed by automated satellites. Although Shuttle flight duration will be limited to periods from seven to thirty days, substantial data can be obtained with a single instrument on short missions, if targets are carefully selected and prioritized, and a large number of instruments can be accommodated on a single flight. Important astronomical data are regularly obtained on sounding rocket flights of five minutes duration. Spacelab will provide far longer observing periods for large and small telescopes, with resources greatly exceeding those of sounding rockets, while retaining much of the sounding rocket philosophy in terms of instrument flexibility, simplicity, reliability assurance and development costs. The Ultraviolet and Optical Astronomy Program on Spacelab is being planned to provide optical astronomers with relatively simple and regular access to the extended wavelength coverage, the superior image quality and the darkness of the night sky available above the earth's atmosphere. In a rapidly evolving science one cannot predict what problems will be timely in the 1980s. Extrapolating from the current epoch, however, one can envision a continuing interest in such areas as the structure, composition and phenomenology of planetary surfaces and atmospheres; the composition and physical nature of the interstellar medium; the composition, structure and life history of stars, especially those in advanced stages of evolution; the stellar population of other galaxies; such enigmatic phenomena as X-ray binary black holes, pulsars, active galactic nuclei and quasars; large scale interactions between galaxies and the nature of the intergalactic medium; precise calibration of the Hubble law for the expansion of the universe; the average density of the universe; and the existence of extraterrestrial life.

Source record↗

DOE OSTI2025

A framework for challenges and solutions in biodesign research

The bioeconomy represents an advanced economic paradigm that builds upon previous agricultural, industrial, and digital economic models. It seeks to tackle critical global challenges such as resource scarcity, escalating healthcare demands, and environmental degradation. At the heart of the bioeconomy is biomanufacturing, which uses natural or engineered enzymes or cell factories built from biological components like promoters, terminators, regulatory sequences, reporters, and functional genes into various chassis hosts (including animal, microbial, plant, and de novo systems) to create products such as food, energy, medicine, materials, chemicals, and engineered tissue/organs. An enabler of biomanufacturing is biodesign – also known as biosystems design and closely related to synthetic biology or engineering biology. This interdisciplinary field aims to understand and predictably modify existing life forms or create entirely new biological entities/systems using rational engineering strategies and automated design tools. Through these capabilities, biodesign supports the discovery, optimization, and creation of efficient platforms for biomanufacturing.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Dynamic Facade Dashboard v0.1.0

The dashboard is a useful tool for early-stage building design decision-making and communication, as it can help users quickly compare the energy and non-energy related performance of various automated, integrated facade systems using a library of pre-computed data. Users can explore the impacts of various design choices by selecting different facade glazing and shading systems, facade control strategies, and lighting control strategies across multiple climate zones. The dashboard instantly visualizes key metrics, including energy usage in HVAC and lighting, peak cooling and heating load, and daylight availability, allowing immediate trade-off analysis to optimize building efficiency and comfort.

Yu, Tammie [Lawrence Berkeley National Laboratory ↗

DOE OSTI2025

BOPTest As a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

DOE OSTI2025

BOPTEST as a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Paul, Lazlo↗

NASA NTRS2006

System Would Acquire Core and Powder Samples of Rocks

A system for automated sampling of rocks, ice, and similar hard materials at and immediately below the surface of the ground is undergoing development. The system, denoted a sample preparation, acquisition, handling, and delivery (SPAHD) device, would be mounted on a robotic exploratory vehicle that would traverse the terrain of interest on the Earth or on a remote planet. The SPAHD device would probe the ground to obtain data for optimization of sampling, prepare the surface, acquire samples in the form(s) of cores and/or powdered cuttings, and deliver the samples to a selected location for analysis and/or storage.

Bar-Cohen, Yoseph↗

NASA NTRSDate not supplied

Integration of Design Data Into Automated Fiber Placement Process Planning Metrics

With the ever-expanding aviation industry, a need is arising for more rapid production of composite aircraft to meet increasing demand. State-of-the-art aircraft such as the Boeing 787showcase 50% composite material usage by weight, highlighting this emerging industry-wide adoption of the material system. Currently, many of the large structures associated with these aircraft are manufactured additively via Automated Fiber Placement (AFP). The AFP process shows great potential for efficient manufacturing, however unavoidable defects still occur because of tool surface geometry, placement errors, or poor process planning, resulting in decreased quality and throughput. Due to such effects, it is critical to incorporate design for manufacturing (DFM) principles to achieve the optimal manufacturing plan and resulting structure. This work will develop a methodology for incorporating design information into process planning metrics in an automated fashion to achieve an optimal set of process inputs.The analysis incorporates HyperX, Computer Aided Process Planning (CAPP) and Vericut Composite Programming (VCP). Safety margins from HyperX are imported into CAPP where AFP defects are mapped to the values. The resulting margins are then incorporated into the CAPP manufacturability algorithms, creating a design informed process planning analysis

Automated Fiber Placement↗

DOE OSTI2023

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e

We introduce a novel Proximal Policy Optimization (PPO) algorithm aimed at addressing the challenge of maintaining a uniform proton beam intensity delivery in the Muon to Electron Conversion Experiment (Mu2e) at Fermi National Accelerator Laboratory (Fermilab). Our primary objective is to regulate the spill process to ensure a consistent intensity profile, with the ultimate goal of creating an automated controller capable of providing real-time feedback and calibration of the Spill Regulation System (SRS) parameters on a millisecond timescale. We treat the Mu2e accelerator system as a Markov Decision Process suitable for Reinforcement Learning (RL), utilizing PPO to reduce bias and enhance training stability. A key innovation in our approach is the integration of a neuralized Proportional-Integral-Derivative (PID) controller into the policy function, resulting in a significant improvement in the Spill Duty Factor (SDF) by 13.6%, surpassing the performance of the current PID controller baseline by an additional 1.6%. This paper presents the preliminary offline results based on a differentiable simulator of the Mu2e accelerator. It paves the groundwork for real-time implementations and applications, representing a crucial step towards automated proton beam intensity control for the Mu2e experiment.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Potential annual daylighting performance of a high-efficiency daylight redirecting slat system

While the primary role of window attachments is often to moderate glare and solar heat gains, they are also able to provide additional daylight to interior spaces. For this purpose, a variety of daylight-redirecting window systems have been developed over the past 150 years. Fixed reflective systems (slats/light shelves) or prismatic systems that rely on total internal reflection work well under specific solar conditions, but generally sacrifice performance over a much wider range of incident solar angles and sky conditions. Dynamic systems - typically reflective slats - are more responsive to sun angles but have not been able to achieve optimal performance for glare and daylight redirection efficiency. A previous investigation into an adjustable, reflective blind concept first conceived of in the late 1970s showed promise but was not reduced to practice due to lack of adequate simulation and analysis tools. In this paper, this concept is further developed and its energy and visual comfort performance evaluated for four mid-latitude, temperate climates using ray-tracing simulation techniques. Overall, results indicate significant potential lighting energy savings when compared with conventional automated reflective blinds (2.1–4.9 kWh/(m 2 ·a), or 14%–42%, depending on climate and orientation) or, especially, manually-operated matte white venetian blinds (1.4–7.9 kWh/(m 2 ·a), or 9%–54%, depending on climate and orientation), while maintaining acceptable or better visual comfort conditions throughout the interior space.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

High Density Vertiplex: Scalable Autonomous Operations Prototype Assessment Simulation

Urban Air Mobility (UAM) is a rapidly growing topic within the field of aviation because of the impact a refined ecosystem and uncrewed aerial vehicles could have on modern society, such as urban air mobility, cargo, and emergency transport. Before the UAM concept can be actualized, research is needed to understand how to integrate these new classes of vehicles and operations into the National Airspace System. One under-researched but critical piece of infrastructure required for UAM operations is Vertiport operations. Vertiports are the envisioned takeoff and landing locations for these uncrewed aerial vehicles. To accommodate the high use of the vertiport, new technologies and roles will be required for optimal use. At NASA, the High Density Vertiplex sub-project targets research into vertiports. The High Density Vertiplex team created an Urban Air Mobility ecosystem to test and evaluate different concepts and tools used to support higher density operations at vertiports. Part of the test and evaluation included the Prototype Assessment Operations simulation of highdensity operations around a vertiport to study vertiport management and vertiport operations. The research team also evaluated how the prototype Urban Air Mobility ecosystem supported fleet managers, ground control station operators, and vertiport managers in execution of nominal and off-nominal high-density operations. Results from this simulation provided insight regarding UAM ecosystem research and development and vertiport automation systems.

Small Uncrewed Aerial Vehicle (sUAS)↗

NASA NTRS1977

Conceptual definition of Automated Power Systems Management

Automated Power Systems Management (APSM) is defined as the capability of a spacecraft power system to automatically perform monitoring, computational, command, and control functions without ground intervention. Power systems for future planetary spacecraft must have this capability because they must perform up to 10 years, and accommodate real-time changes in mission execution autonomously. Specific APSM functions include fault detection, isolation, and correction; system performance and load profile prediction; power system optimization; system checkout; and data storage and transmission control. This paper describes the basic method of implementing these specific functions. The APSM hardware includes a central power system computer and a processor dedicated to each major power system subassembly along with digital interface circuitry. The major payoffs anticipated are in enhancement of spacecraft reliability and life and reduction of overall spacecraft program cost.

Imamura, M. S.↗

NASA NTRS2017

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Numerical Analysi↗

NASA NTRS2026

Smart Process Planning for Automated Fiber Placement

Many industries, including aerospace, automotive, wind energy, maritime, and sporting goods, rely on strong, lightweight materials called composites. These materials are made by layering fibers, which can come in the form of narrow strips or wider sheets, and setting them in a polymer matrix. One of the most advanced ways to make these parts is through automated fiber placement, where a machine lays down the fibers in precise patterns. This method can create very efficient and strong designs, but it is complex, expensive, and often depends heavily on the experience of skilled engineers. Today, the design, manufacturing, and inspection stages of composite production are usually handled separately. This separation means that important information, such as how a part will be built or what defects might occur, is not always shared between stages. As a result, parts may not be as lightweight, strong, or defect-free as possible, and the process can take longer and cost more. This research develops a smart process planning system that connects design, manufacturing, and inspection into one continuous process. Built as software that works with existing tools, the system can automatically plan how the fibers are placed, predicting and reducing defects while improving both manufacturability and strength. The system optimizes not only individual layers but also how defects are distributed across all layers, preventing them from stacking up in ways that weaken the final part. It also uses inspection results from completed parts to improve future designs, creating a feedback loop where each stage informs the others. The system was tested by designing a composite panel using this new approach and comparing it to a panel made with state-of-the-art manual planning methods. The results showed that the system could intentionally control where defects appeared and increase the efficiency of the planning process. By unifying design, manufacturing, and inspection, this research shows a way to make advanced composite manufacturing more efficient, consistent, and cost-effective. This approach lowers the barrier to using automated fiber placement and opens the door for its wider adoption not only in aerospace but also in industries such as automotive, wind energy, maritime, and sporting goods, where strong and lightweight structures are essential.

Computer-Aided Process Planning↗

NASA NTRSDate not supplied

The Inspectability Metric: A Formalized System Of Measurement Enabling The Design For Inspection Framework

Nondestructive evaluation (NDE) engineers are often confronted with structural design choices that present challenges to meeting inspection requirements. These challenges, at best, increase the resources needed to design an inspection solution and, at worst, require resource intensive redesign of the structure. If the inspectability of the structure can be determined early in the design cycle, these challenging inspection scenarios can be avoided. The emergence of additive manufacturing has further compounded this problem by enabling the creation of highly optimized structures with no regard to inspection constraints. Design for inspection (DFI) offers a framework to integrate nondestructive evaluation (NDE) into the design process to alleviate the mechanisms that produce uninspectable designs. DFI is the concept of including inspectability in a multi-objective optimization framework so that it can be considered in parallel to other metrics such as mass and manufacturability. This allows rapid evaluation of the trade-off between design metrics to find solutions that meet the inspection needs of a particular material system, structural concept, or vehicle program. To enable DFI, there must be a system by which the inspectability of a structure can be measured. This system must be agile to produce results quickly, it must be versatile to work with the type of incomplete information one would encounter early in the design process (such as lack of inspection requirements), and it must be delivered in a form that is easily understood by designers. To meet this need, this presentation introduces the novel inspectability metric as a system to measure inspectability. The inspectability metric is a standardized, automation friendly procedure that uses simulations to determine inspectability. Along with guidelines to properly process designs and integrate with existing workflows, the inspectability metric provides a suite of simulation tests to interrogate the ability to find defects and the sensitivity to variability. The testing rubric is designed to maximize the coverage of the parameter space while minimizing the number of simulations needed. The inspectability metric has been in development in collaboration with industry partners to ensure compatibility with modern simulation tools and aerospace design workflows. In this study, we will demonstrate how the inspectability metric is able to determine the inspectability of multiple types of structures, including aerospace composites and additively manufactured parts. We will then show how the inspectability score can be plugged into existing design optimization tasks, such as structural sizing algorithms or design for manufacturing (DFM) frameworks.

Design for inspection↗

NASA NTRS1978

Array automated assembly task, phase 2. Low cost silicon solar array project

Several modifications instituted in the wafer surface preparation process served to significantly reduce the process cost to 1.55 cents per peak watt in 1975 cents. Performance verification tests of a laser scanning system showed a limited capability to detect hidden cracks or defects, but with potential equipment modifications this cost effective system could be rendered suitable for applications. Installation of electroless nickel plating system was completed along with an optimization of the wafer plating process. The solder coating and flux removal process verification test was completed. An optimum temperature range of 500-550 C was found to produce uniform solder coating with the restriction that a modified dipping procedure is utilized. Finally, the construction of the spray-on dopant equipment was completed.

Rhee, S. S.↗

DOE OSTI2025

Beyond Optimization: Exploring Novelty Discovery in Autonomous Experiments

Autonomous experiments (AEs) are transforming how scientific research is conducted by integrating artificial intelligence with automated experimental platforms. Current AEs primarily focus on the optimization of a predefined target; while accelerating this goal, such an approach limits the discovery of unexpected or unknown physical phenomena. Here, we introduce a novel framework, INS 2 ANE (Integrated Novelty Score−Strategic Autonomous Non-Smooth Exploration), to enhance the discovery of novel phenomena in autonomous microscopy experimentation. Our method integrates two key components: (1) a novelty scoring system that evaluates the uniqueness of experimental results and (2) a strategic sampling mechanism that promotes exploration of under-sampled regions even if they appear less promising by conventional criteria. We validate this approach on a preacquired data set with a known ground truth comprising of image−spectral pairs. We further implement the process on autonomous scanning probe microscopy experiments. INS 2 ANE significantly increases the diversity of explored phenomena in comparison to conventional optimization routines, enhancing the likelihood of discovering previously unobserved phenomena. These results demonstrate the potential for autonomous microscopy experiments to enhance the scientific discovery by navigating complex experimental spaces to uncover novel phenomena.

Materials↗