Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “architecture 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.

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

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Modeling of Euclidean braided fiber architectures to optimize composite properties

Three-dimensional braided fiber reinforcements are a very effective toughening mechanism for composite materials. The integral yarn path inherent to this fiber architecture allows for effective multidirectional dispersion of strain energy and negates delamination problems. In this paper a geometric model of Euclidean braid fiber architectures is presented. This information is used to determine the degree of geometric isotropy in the braids. This information, when combined with candidate material properties, can be used to quickly generate an estimate of the available load-carrying capacity of Euclidean braids at any arbitrary angle.

Armstrong-Carroll, E.↗
NASA NTRS1989

Design for steering accuracy in antenna arrays using shared optical phase shifters

Uniform linear phased arrays where many radiating elements share a relatively small number of phase shifters are investigated. Such architectures arise in arrays which derive the time delays in the signal paths from a small group of independent phase shifters. In particular, a true time-delay device which has been suggested recently for optically controlled arrays is used as the basic phase shifter. Different architectures, viz. alternative procedures of deriving the necessary time delay for each antenna in the face of phase-shifter inaccuracies, are examined. The variance of the steered beam's direction is used as the performance criterion. The direction-optimal architecture is obtained by means of quadratic programming, and is shown not to be unique. The nonuniqueness of the optimal architecture is exploited to improve other characteristics of the array's beam shape, and the optimal solution is shown to compare favorably with a suboptimal interleaved solution which is easier to implement.

Kam, Moshe↗
DOE OSTI2023

Multidisciplinary design optimization in Architecture, Engineering, and Construction: a detailed review and call for collaboration

The design of buildings has become a complex and multidisciplinary problem involving multiple conflicting objectives as architects and designers address competing technical, economic, environmental, and societal concerns. This has been driving research in Architecture, Engineering, and Construction (AEC) toward rigorous multidisciplinary decision-making frameworks that generate and evaluate numerous design alternatives using multi-objective optimization in concert with simulation and analysis models of varying fidelity and computational expense. While such frameworks are well known and widely employed in the aerospace and systems engineering domains, efforts by design professionals and researchers in the AEC field are scattered at best. In this paper, we provide a detailed review of recent developments in optimization frameworks in the AEC field and subsequently highlight how such developments are largely compartmentalized into separate domains such as structural, energy, daylighting, and other performance factors. Herein, we further discuss the technical challenges involved in concurrent coupled multidisciplinary design optimization (MDO) in the AEC field such as interoperability issues between Building Information Modeling (BIM) environments, analysis/simulation tools, and optimization frameworks. We conclude by outlining research needed for more unified modeling and simulation-based optimization frameworks to aid in complex and multidisciplinary building design processes. We also highlight the need for the identification and development of multi-fidelity simulation tools for use across multiple design phases. As such, this paper contributes a novel roadmap to leverage aerospace and systems engineering research in MDO into the field of AEC, along with a call for researchers in the MDO community to seek collaborations in AEC field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2002

The Aeronautical Data Link: Taxonomy, Architectural Analysis, and Optimization

The future Communication, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) System will rely on global satellite navigation, and ground-based and satellite based communications via Multi-Protocol Networks (e.g. combined Aeronautical Telecommunications Network (ATN)/Internet Protocol (IP)) to bring about needed improvements in efficiency and safety of operations to meet increasing levels of air traffic. This paper will discuss the development of an approach that completely describes optimal data link architecture configuration and behavior to meet the multiple conflicting objectives of concurrent and different operations functions. The practical application of the approach enables the design and assessment of configurations relative to airspace operations phases. The approach includes a formal taxonomic classification, an architectural analysis methodology, and optimization techniques. The formal taxonomic classification provides a multidimensional correlation of data link performance with data link service, information protocol, spectrum, and technology mode; and to flight operations phase and environment. The architectural analysis methodology assesses the impact of a specific architecture configuration and behavior on the local ATM system performance. Deterministic and stochastic optimization techniques maximize architectural design effectiveness while addressing operational, technology, and policy constraints.

Morris, A. Terry↗
DOE OSTI2025

Root architectural plasticity optimizes nutrient acquisition in switchgrass under variable phosphorus forms

Aims Understanding the influence of different forms of phosphorus (P) over the different root traits and how those traits are related to increasing the efficiency of nutrient acquisition strategies. Methods Investigation of switchgrass (Panicum virgatum L.) root morphology responses to inorganic P (Pi) soluble (Potassium-P), insoluble (Aluminum-P), and organic P (Po) (Inositol Hexa-Phosphate, IHex-P) in rhizoboxes. Roots were traced over the root box and scanned using WinRhizoTM. The CRootbox model was employed to simulate root growth. Results Significant plasticity observed under IHex-P treatment, with a 46% increase in root branching, leading to a 74% rise in total root length and a 65% increase in root surface area compared to inorganic P forms. IHex-P resulted in a 73% higher root biomass than Aluminum-P and a 26% increase compared to Potassium-P. Most of the differences were attributed to the elongation of root branches. Conclusions Here, the study emphasizes the dynamic nature of switchgrass root architecture and morphology in response to varying P forms in the soil. The absence of Pi in the soil triggered increased plasticity in root traits, facilitating root access to Po and uptake of P. These findings offer valuable insights into the adaptive mechanisms of perennial plants, with significant implications for optimizing nutrient acquisition strategies in both agricultural and natural ecosystems.

Organic phosphorus↗
DOE OSTI2024

A Performance-Portable MultiGPU Implementation of 3D Euler Equations using ProtoX and IRIS

Computational scientists often face challenges when developing and optimizing code for high-performance computing (HPC), especially when trying to leverage GPUs. Given the heterogeneity of the nodes that comprise many modern HPC facilities, considerable demand exists for performance portable solutions for the core computational kernels used in many scientific computing libraries. In this work, we demonstrate a fourth-order finite volume method–based implementation of the Euler equations, which are an integral part of computational fluid dynamics. Our performance-portable multiGPU implementation for Euler equations uses ProtoX to generate kernels and IRIS for portability. ProtoX is a domain-specific language that uses a structured-grid partial differential equation library called Proto as its front end and the SPIRAL code generation system as its back end to generate optimized kernels for different architectures. Optimized kernels generated by ProtoX are orchestrated through the IRIS intelligent runtime system to provide portability. Two levels of optimizations within the IRIS runtime— directed acyclic graph fusion and task fusion—are explored to efficiently utilize computing resources in a multiGPU environment. Performance improvement through these optimizations is showcased by comparing the base ProtoX-IRIS implementation on AMD GPUs (Frontier node) and on NVIDIA GPUs (NVIDIA DGX-1).

Mankad, Het↗
NASA NTRS2006

Efficient and Robust Data Collection Using Compact Micro Hardware, Distributed Bus Architectures and Optimizing Software

Future In-Space propulsion systems for exploration programs will invariably require data collection from a large number of sensors. Consider the sensors needed for monitoring several vehicle systems states of health, including the collection of structural health data, over a large area. This would include the fuel tanks, habitat structure, and science containment of systems required for Lunar, Mars, or deep space exploration. Such a system would consist of several hundred or even thousands of sensors. Conventional avionics system design will require these sensors to be connected to a few Remote Health Units (RHU), which are connected to robust, micro flight computers through a serial bus. This results in a large mass of cabling and unacceptable weight. This paper first gives a survey of several techniques that may reduce the cabling mass for sensors. These techniques can be categorized into four classes: power line communication, serial sensor buses, compound serial buses, and wireless network. The power line communication approach uses the power line to carry both power and data, so that the conventional data lines can be eliminated. The serial sensor bus approach reduces most of the cabling by connecting all the sensors with a single (or redundant) serial bus. Many standard buses for industrial control and sensor buses can support several hundreds of nodes, however, have not been space qualified. Conventional avionics serial buses such as the Mil-Std-1553B bus and IEEE 1394a are space qualified but can support only a limited number of nodes. The third approach is to combine avionics buses to increase their addressability. The reliability, EMI/EMC, and flight qualification issues of wireless networks have to be addressed. Several wireless networks such as the IEEE 802.11 and Ultra Wide Band are surveyed in this paper. The placement of sensors can also affect cable mass. Excessive sensors increase the number of cables unnecessarily. Insufficient number of sensors may not provide adequate coverage of the system. This paper also discusses an optimal technique to place and validate sensors.

micro hardware↗
NASA NTRS2008

NASA Tech Briefs, January 2008

Topics covered include: Induction Charge Detector with Multiple Sensing Stages; Generic Helicopter-Based Testbed for Surface Terrain Imaging Sensors; Robot Electronics Architecture; Optimized Geometry for Superconducting Sensing Coils; Sensing a Changing Chemical Mixture Using an Electronic Nose; Inertial Orientation Trackers with Drift Compensation; Microstrip Yagi Antenna with Dual Aperture-Coupled Feed; Patterned Ferroelectric Films for Tunable Microwave Devices; Micron-Accurate Laser Fresnel-Diffraction Ranging System; Efficient G(sup 4)FET-Based Logic Circuits; Web-Enabled Optoelectronic Particle-Fallout Monitor; SiO2/TiO2 Composite for Removing Hg from Combustion Exhaust; Lightweight Tanks for Storing Liquefied Natural Gas; Hybrid Wound Filaments for Greater Resistance to Impacts; Making High-Tensile-Strength Amalgam Components; Bonding by Hydroxide-Catalyzed Hydration and Dehydration; Balanced Flow Meters without Moving Parts; Deflection-Compensating Beam for Use inside a Cylinder; Four-Point-Latching Microactuator; Curved Piezoelectric Actuators for Stretching Optical Fibers; Tunable Optical Assembly with Vibration Dampening; Passive Porous Treatment for Reducing Flap Side-Edge Noise; Cylindrical Piezoelectric Fiber Composite Actuators; Patterning of Indium Tin Oxide Films; Gimballed Shoulders for Friction Stir Welding; Improved Thermal Modulator for Gas Chromatography; Nuclear-Spin Gyroscope Based on an Atomic Co-Magnetometer; Utilizing Ion-Mobility Data to Estimate Molecular Masses; Optical Displacement Sensor for Sub-Hertz Applications; Polarization/Spatial Combining of Laser-Diode Pump Beams; Spatial Combining of Laser-Diode Beams for Pumping an NPRO; Algorithm Optimally Orders Forward-Chaining Inference Rules; Project Integration Architecture; High Power Amplifier and Power Supply; Estimating Mixing Heights Using Microwave Temperature Profiler; and Multiple-Cone Sunshade for a Spaceborne Telescope.

Source record↗
NASA NTRS2004

FY04 Advanced Life Support Architecture and Technology Studies: Mid-Year Presentation

Long-Term Objective: Identify optimal advanced life support system designs that meet existing and projected requirements for future human spaceflight missions. a) Include failure-tolerance, reliability, and safe-haven requirements. b) Compare designs based on multiple criteria including equivalent system mass (ESM), technology readiness level (TRL), simplicity, commonality, etc. c) Develop and evaluate new, more optimal, architecture concepts and technology applications.

Lange, Kevin↗
DOE OSTI2021

Explainable Neural Architecture Search (XNAS)

Code for the paper Learning Interpretable Models Through Multi-Objective Neural Architecture Search by Zachariah Carmichael, Tim Moon, and Sam Ade Jacobs. Monumental advances in deep learning have led to unprecedented achievements across a multitude of domains. While the performance of deep neural networks is indubitable, the architectural design and interpretability of such models are nontrivial. Research has been introduced to automate the design of neural network architectures through neural architecture search (NAS). Recent progress has made these methods more pragmatic by exploiting distributed computation and novel optimization algorithms. However, there is little work in optimizing architectures for interpretability. To this end, we propose a multiobjective distributed NAS framework that optimizes for both task performance and introspection. We leverage the non-dominated sorting genetic algorithm (NSGA-II) and explainable AI (XAI) techniques to reward architectures that can be better comprehended by humans. The framework is evaluated on several image classification datasets. We demonstrate that jointly optimizing for introspection ability and task error leads to more disentangled architectures that perform within tolerable error.

Carmichael, ZachariahJ↗
DOE OSTI2020

Toward a scalable robust security-constrained optimal power flow using a proximal projection bundle method

Robust security-constrained optimal power flow (rSCOPF) aims to find the worst-case contingencies of alternating current optimal power flow (ACOPF) in power systems. With the rise of GPU architectures on the upcoming supercomputer architectures, optimization algorithms that rely on sparse linear algebra and indefinite linear systems are becoming increasingly hard to solve efficiently (e.g. interior-point method). To address this we revisit a maximin optimization formulation of the rSCOPF and the single-level mixed-integer semidefinite programming (MISDP) reformulation, which is obtained by taking the Lagrangian relaxation of the inner minimization ACOPF problem. In this paper, we focus on the development of a proximal projection bundle method (PPBM) for solving continuous relaxation node subproblems of the MISDP problem, based primarily on the well-known alternating direction method of multipliers. Cutting planes reminiscent of bundle method ideas are also applied in coordination with updates of the proximal parameter. The cutting-plane method can generate a large number of linear inequalities, leading to a large scale but decomposable quadratic programming (QP) subproblem that is amenable to GPUs. We present the numerical results on the IEEE 30, 57, 118, and 300-bus systems by using our PBMM method. We discuss the main computational bottleneck of our method, which is the time taken to solve each iteration of a QP subproblem instance of the PPBM, and how GPU architectures can accelerate this solution process.

bundle method↗
NASA NTRS1989

Electro-optic architecture (EOA) for sensors and actuators in aircraft propulsion systems

Results of a study to design an optimal architecture for electro-optical sensing and control in advanced aircraft and space systems are described. The propulsion full authority digital Electronic Engine Control (EEC) was the focus for the study. The recommended architecture is an on-engine EEC which contains electro-optic interface circuits for fiber-optic sensors on the engine. Size and weight are reduced by multiplexing arrays of functionally similar sensors on a pair of optical fibers to common electro-optical interfaces. The architecture contains common, multiplex interfaces to seven sensor groups: (1) self luminous sensors; (2) high temperatures; (3) low temperatures; (4) speeds and flows; (5) vibration; (6) pressures; and (7) mechanical positions. Nine distinct fiber-optic sensor types were found to provide these sensing functions: (1) continuous wave (CW) intensity modulators; (2) time division multiplexing (TDM) digital optic codeplates; (3) time division multiplexing (TDM) analog self-referenced sensors; (4) wavelength division multiplexing (WDM) digital optic code plates; (5) wavelength division multiplexing (WDM) analog self-referenced intensity modulators; (6) analog optical spectral shifters; (7) self-luminous bodies; (8) coherent optical interferometers; and (9) remote electrical sensors. The report includes the results of a trade study including engine sensor requirements, environment, the basic sensor types, and relevant evaluation criteria. These figures of merit for the candidate interface types were calculated from the data supplied by leading manufacturers of fiber-optic sensors.

Glomb, W. L., Jr.↗
NASA NTRS1999

Analog Module Architecture for Space-Qualified Field-Programmable Mixed-Signal Arrays

Spacecraft require all manner of both digital and analog circuits. Onboard digital systems are constructed almost exclusively from field-programmable gate array (FPGA) circuits providing numerous advantages over discrete design including high integration density, high reliability, fast turn-around design cycle time, lower mass, volume, and power consumption, and lower parts acquisition and flight qualification costs. Analog and mixed-signal circuits perform tasks ranging from housekeeping to signal conditioning and processing. These circuits are painstakingly designed and built using discrete components due to a lack of options for field-programmability. FPAA (Field-Programmable Analog Array) and FPMA (Field-Programmable Mixed-signal Array) parts exist but not in radiation-tolerant technology and not necessarily in an architecture optimal for the design of analog circuits for spaceflight applications. This paper outlines an architecture proposed for an FPAA fabricated in an existing commercial digital CMOS process used to make radiation-tolerant antifuse-based FPGA devices. The primary concerns are the impact of the technology and the overall array architecture on the flexibility of programming, the bandwidth available for high-speed analog circuits, and the accuracy of the components for high-performance applications.

Edwards, R. Timothy↗
NASA NTRS2011

Design Considerations for a Dedicated Gravity Recovery Satellite Mission Consisting of Two Pairs of Satellites

Future satellite missions dedicated to measuring time-variable gravity will need to address the concern of temporal aliasing errors; i.e., errors due to high-frequency mass variations. These errors have been shown to be a limiting error source for future missions with improved sensors. One method of reducing them is to fly multiple satellite pairs, thus increasing the sampling frequency of the mission. While one could imagine a system architecture consisting of dozens of satellite pairs, this paper explores the more economically feasible option of optimizing the orbits of two pairs of satellites. While the search space for this problem is infinite by nature, steps have been made to reduce it via proper assumptions regarding some parameters and a large number of numerical simulations exploring appropriate ranges for other parameters. A search space originally consisting of 15 variables is reduced to two variables with the utmost impact on mission performance: the repeat period of both pairs of satellites (shown to be near-optimal when they are equal to each other), as well as the inclination of one of the satellite pairs (the other pair is assumed to be in a polar orbit). To arrive at this conclusion, we assume circular orbits, repeat groundtracks for both pairs of satellites, a 100-km inter-satellite separation distance, and a minimum allowable operational satellite altitude of 290 km based on a projected 10-year mission lifetime. Given the scientific objectives of determining time-variable hydrology, ice mass variations, and ocean bottom pressure signals with higher spatial resolution, we find that an optimal architecture consists of a polar pair of satellites coupled with a pair inclined at 72deg, both in 13-day repeating orbits. This architecture provides a 67% reduction in error over one pair of satellites, in addition to reducing the longitudinal striping to such a level that minimal post-processing is required, permitting a substantial increase in the spatial resolution of the gravity field products. It should be emphasized that given different sets of scientific objectives for the mission, or a different minimum allowable satellite altitude, different architectures might be selected.

Wiese, D. N.↗
DOE OSTI2022

An Accuracy-Maximization Approach for Claims Classifiers in Document Content Analytics for Cybersecurity

This paper presents our research approach and findings towards maximizing the accuracy of our classifier of feature claims for cybersecurity literature analytics, and introduces the resulting model ClaimsBERT. Its architecture, after extensive evaluations of different approaches, introduces a feature map concatenated with a Bidirectional Encoder Representation from Transformers (BERT) model. We discuss deployment of this new concept and the research insights that resulted in the selection of Convolution Neural Networks for its feature mapping aspects. We also present our results showing ClaimsBERT to outperform all other evaluated approaches. This new claims classifier represents an essential processing stage within our vetting framework aiming to improve the cybersecurity of industrial control systems (ICS). Furthermore, in order to maximize the accuracy of our new ClaimsBERT classifier, we propose an approach for optimal architecture selection and determination of optimized hyperparameters, in particular the best learning rate, number of convolutions, filter sizes, activation function, the number of dense layers, as well as the number of neurons and the drop-out rate for each layer. Fine-tuning these hyperparameters within our model led to an increase in classification accuracy from 76% obtained with BertForSequenceClassification’s original model to a 97% accuracy obtained with ClaimsBERT.

Ameri, Kimia (ORCID:0000000328791871)↗