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The ILLIAC-4 hardware is described. The Illiac system, the Advanced Research Projects Agency computer network, and IMLAC PDS-1 are included. The space shuttle flow simulation is demonstrated to show the feasibility of using an advanced computer from a remote location.
The requirements and opportunities for technological development in transport aircraft of the next generation are reviewed, focusing primarily on conventional, subsonic aircraft. Advances in computational aerodynamics and computer-aided design and manufacturing (in numerically controlled processes) are noted as well as improved wind tunnel testing and drag reduction techniques. Advances in aeroelasticity prediction have made it possible to use flexible, high-aspect-ratio wings without large weight penalties. Weight reduction may be achieved by the use of composite aircraft structures and superplastic forming combined with diffusion bonding, however composites require improvement in manufacturing techniques and mechanical properties in order to gain general acceptance. Propulsion systems can be improved in engine fuel efficiency, control, durability, environmental compatibility (exhaust and noise emissions), and fuel specifications. In avionics, due to the growth of low-cost, miniaturized packages, opportunities exist in the fields of digital controls, navigation, guidance and communication. Applications of new technologies to various aspects of flight safety are also outlined.
Computational aerothermodynamics (CAT) has in the past contributed to the understanding of real-gas flows encountered by hypervelocity reentry vehicles. With advances in computational fluid dynamics, in the modeling of high temperature phenomena, and in computer capability, CAT is an enabling technology for the design of many future space vehicles. An overview of the current capabilities of CAT is provided by describing available methods and their applications. Technical challenges that need to be met are discussed.
Computational aerothermodynamics (CAT) has in the past contributed to the understanding of real-gas flows encountered by hypervelocity reentry vehicles. With advances in computational fluid dynamics, in the modeling of high temperature phenomena, and in computer capability, CAT is an enabling technology for the design of many future space vehicles. An overview of the current capabilities of CAT is provided by describing available methods and their applications. Technical challenges that need to be met are discussed.
This publication contains the proceedings of the Fourth Computational Aeroacoustics (CAA) Workshop on Benchmark Problems. In this workshop, as in previous workshops, the problems were devised to gauge the technological advancement of computational techniques to calculate all aspects of sound generation and propagation in air directly from the fundamental governing equations. A variety of benchmark problems have been previously solved ranging from simple geometries with idealized acoustic conditions to test the accuracy and effectiveness of computational algorithms and numerical boundary conditions; to sound radiation from a duct; to gust interaction with a cascade of airfoils; to the sound generated by a separating, turbulent viscous flow. By solving these and similar problems, workshop participants have shown the technical progress from the basic challenges to accurate CAA calculations to the solution of CAA problems of increasing complexity and difficulty. The fourth CAA workshop emphasized the application of CAA methods to the solution of realistic problems. The workshop was held at the Ohio Aerospace Institute in Cleveland, Ohio, on October 20 to 22, 2003. At that time, workshop participants presented their solutions to problems in one or more of five categories. Their solutions are presented in this proceedings along with the comparisons of their solutions to the benchmark solutions or experimental data. The five categories for the benchmark problems were as follows: Category 1:Basic Methods. The numerical computation of sound is affected by, among other issues, the choice of grid used and by the boundary conditions. Category 2:Complex Geometry. The ability to compute the sound in the presence of complex geometric surfaces is important in practical applications of CAA. Category 3:Sound Generation by Interacting With a Gust. The practical application of CAA for computing noise generated by turbomachinery involves the modeling of the noise source mechanism as a vortical gust interacting with an airfoil. Category 4:Sound Transmission and Radiation. Category 5:Sound Generation in Viscous Problems. Sound is generated under certain conditions by a viscous flow as the flow passes an object or a cavity.
The potential of fuzzy sets and neural networks, often referred to as soft computing, for aiding in all aspects of manufacturing of advanced materials like ceramics is addressed. In design and manufacturing of advanced materials, it is desirable to find which of the many processing variables contribute most to the desired properties of the material. There is also interest in real time quality control of parameters that govern material properties during processing stages. The concepts of fuzzy sets and neural networks are briefly introduced and it is shown how they can be used in the design and manufacturing processes. These two computational methods are alternatives to other methods such as the Taguchi method. The two methods are demonstrated by using data collected at NASA Lewis Research Center. Future research directions are also discussed.
This document describes the computational aspects of propeller noise prediction in the time domain and the use of high speed propeller noise prediction program ASSPIN (Advanced Subsonic and Supersonic Propeller Induced Noise). These formulations are valid in both the near and far fields. Two formulations are utilized by ASSPIN: (1) one is used for subsonic portions of the propeller blade; and (2) the second is used for transonic and supersonic regions on the blade. Switching between the two formulations is done automatically. ASSPIN incorporates advanced blade geometry and surface pressure modelling, adaptive observer time grid strategies, and contains enhanced numerical algorithms that result in reduced computational time. In addition, the ability to treat the nonaxial inflow case has been included.
Turbulence modeling continues to be one of the most difficult problems in fluid mechanics. Existing prediction methods are well developed for certain classes of simple equilibrium flows, but are still not entirely satisfactory for a large category of complex non-equilibrium flows found in engineering practice. Direct and large-eddy simulation (LES) approaches have long been believed to have great potential for the accurate prediction of difficult turbulent flows, but the associated computational cost has been prohibitive for practical problems. This remains true for direct simulation but is no longer clear for large-eddy simulation. Advances in computer hardware, numerical methods, and subgrid-scale modeling have made it possible to conduct LES for flows or practical interest at Reynolds numbers in the range of laboratory experiments. The objective of this work is to apply ES and the dynamic subgrid-scale model to the flow of a boundary layer over a concave surface.
The successful design of thermal protection systems for vehicles operating in atmosphere and near-space environments requires accurate analyses of heating rate and temperature histories encountered along a trajectory. For preliminary design calculations, however, the requirement for accuracy must be tempered by the need for speed and versatility in computational tools used to determine thermal environments and structural thermal response. The MINIVER program was found to provide the proper balance between versatility, speed and accuracy for an aerothermal prediction tool. The advancement in computer aided design concepts at Langley Research Center (LaRC) in the past few years has made it desirable to incorporate the MINIVER program into the LaRC Advanced Vehicle Integrated Design, AVID, system. In order to effectively incorporate MINIVER into the AVID system, several changes to MINIVER were made. The thermal conduction options in MINIVER were removed and a new Explicit Interactive Thermal Structures (EXITS) code was developed. Many upgrades to the MINIVER code were made and a new Langley version of MINIVER called LANMIN was created.
An external review of the Integrated Technology Plan for the Civil Space Program is presented. The topics are presented in viewgraph form and include the following: onboard memory and storage technology; advanced flight computers; special purpose flight processors; onboard networking and testbeds; information archive, access, and retrieval; visualization; neural networks; software engineering; and flight control and operations.
The topic of this presentation is a multi-center effort to improve the undersanding and characterization of dynamic stability. An assessment of existing experimental and computational tools for characterizing dynamic stability will be discussed. Current state-of-the-art experimental techniques, and known gaps/overlaps between facilities is presented. Finally, advancements in computational capabilities under the direction of ESM is presenting using the Free-Flight CFD solver within US3D.
The successful design of thermal protection systems for vehicles operating in atmosphere and near space environments requires accurate analyses of heating rate and temperature histories encountered along a trajectory. For preliminary design calculations, however, the requirement for accuracy must be tempered by the need for speed and versatility in computational tools used to determine thermal environments and structural thermal response. The MINIVER program has been found to provide the proper balance between versatility, speed and accuracy for an aerothermal prediction tool. The advancement in computer aided design concepts at Langley Research Center (LaRC) in the past few years has made it desirable to incorporate the MINIVER program into the LaRC Advanced Vehicle Integrated Design, AVID, system. In order to effectively incorporate MINIVER into the AVID system, several changes to MINIVER were made. The thermal conduction options in MINIVER were removed and a new Explicit Interactive Thermal Structures (EXITS) code was developed. Many upgrades to the MINIVER code were made and a new Langley version of MINIVER called LANMIN was created. The theoretical methods and subroutine functions used in LANMIN are described.
NASA Langley has a long history of attacking important technical Opportunities from a broad base of supporting disciplines. The research and development at Langley in this subject area range from the test tube to the test flight, The information covered here will range from the development of innovative new materials, sensors and actuators, to the incorporation of smart sensors and actuators in practical devices, to the optimization of the location of these devices, to, finally, a wide variety of applications of these devices utilizing Langley's facilities and expertise. Advanced materials are being developed for sensors and actuators, as well as polymers for integrating smart devices into composite structures. Contributions reside in three key areas: computational materials; advanced piezoelectric materials; and integrated composite structures.
This paper presents a summary of the computational predictions and measurement data contributed to Category 7 of the 3rd AIAA Workshop on Benchmark Problems for Airframe Noise Computations (BANC-III), which was held in Atlanta, GA, on June 14-15, 2014. Category 7 represents the first slat-noise configuration to be investigated under the BANC series of workshops, namely, the 30P30N two-dimensional high-lift model (with a slat contour that was slightly modified to enable unsteady pressure measurements) at an angle of attack that is relevant to approach conditions. Originally developed for a CFD challenge workshop to assess computational fluid dynamics techniques for steady high-lift predictions, the 30P30N configurations has provided a valuable opportunity for the airframe noise community to collectively assess and advance the computational and experimental techniques for slat noise. The contributed solutions are compared with each other as well as with the initial measurements that became available just prior to the BANC-III Workshop. Specific features of a number of computational solutions on the finer grids compare reasonably well with the initial measurements from FSU and JAXA facilities and/or with each other. However, no single solution (or a subset of solutions) could be identified as clearly superior to the remaining solutions. Grid sensitivity studies presented by multiple BANC-III participants demonstrated a relatively consistent trend of reduced surface pressure fluctuations, higher levels of turbulent kinetic energy in the flow, and lower levels of both narrow band peaks and the broadband component of unsteady pressure spectra in the nearfield and farfield. The lessons learned from the BANC-III contributions have been used to identify improvements to the problem statement for future Category-7 investigations.
The Western Area Power Administration (WAPA) plays a vital role in delivering reliable and cost-effective hydroelectric power to millions of customers across the western United States. The Colorado River Storage Project (CRSP) carries out WAPA’s mission in Arizona, Utah, Colorado, New Mexico, Nevada, Wyoming and Texas. Achieving this mission requires effective management of the Colorado River system, and depends on the use of advanced analytical tools and modeling methodologies. For many years, CRSP has relied on the Generation and Transmission Maximization Superlite (GTMax SL) model for its mid-term and long-term hydroscheduling needs. However, the evolving energy market, power system operations, environmental rules, and hydrology conditions, coupled with advancements in computational capabilities, have necessitated the development of a more modern and robust solution. This report introduces the Colorado River Storage Project Python-based (CRiSPPy) model, a new, advanced hydropower scheduling tool developed to address CRSP ever-evolving challenges. CRiSPPy represents a significant leap forward in our ability to model and optimize the operation of the Colorado River system. It incorporates state-of-the-art optimization algorithms, enhanced data management capabilities, and an advanced graphical user interface, providing WAPA CRSP personnel with unprecedented insights and decision-making support. This document details the development, capabilities, and implementation of CRiSPPy. It is intended to serve as a comprehensive resource for WAPA staff, stakeholders, and anyone interested in the future of hydropower scheduling in the Colorado River Basin. We are confident that CRiSPPy will enhance WAPA's mission while adapting to the challenges of a dynamic and increasingly complex environment. The version of CRiSPPy described in this report is the version 2.3. New versions of CRiSPPy will be developed as the tool keeps evolving to address CRSP challenges.
This Perspective builds upon insights from the National Institute of Standards and Technology (NIST)-organized workshop, “Materials and Metrology Needs for Advanced Semiconductor Packaging Strategies,” held at the 35th annual Electronics Packaging Symposium in Binghamton, NY, on September 5, 2024. It outlines critical challenges and opportunities related to polymer-based “soft” materials in advanced semiconductor packaging, with emphasis on polymer science, measurement science (metrology), and the strategic development of Research-Grade Test Materials (RGTMs). These efforts, led by the NIST CHIPS team, aim to advance the fundamental understanding of structure-property-processing relationships, promote standardized guidelines and innovative methods for material characterization, and accelerate the development, qualification, and adoption of next-generation packaging materials. The Perspective also distills key insights from the panel discussion with industry experts, emphasizing the need for close collaboration among materials scientists, process engineers, and metrology experts to enable a holistic strategy, further highlighting the importance of cross-sector partnerships among industry, academia, and government to address pressing challenges in packaging materials and processes.
Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.
The next twenty-five years will see major advances in civil propulsion technology that will result in completely new aircraft systems for domestic, international, commuter and high-speed transports. These aircraft will include advanced aerodynamic, structural, and avionic technologies resulting in major new system capabilities and economic improvements. Propulsion technologies will include high-speed turboprops in the near term, very high bypass ratio turbofans, high efficiency small engines and advanced cycles utilizing high temperature materials for high-speed propulsion. Key fundamental enabling technologies include increased temperature capability and advanced design methods. Increased temperature capability will be based on improved composite materials such as metal matrix, intermetallics, ceramics, and carbon/carbon as well as advanced heat transfer techniques. Advanced design methods will make use of advances in internal computational fluid mechanics, reacting flow computation, computational structural mechanics and computational chemistry. The combination of advanced enabling technologies, new propulsion concepts and advanced control approaches will provide major improvements in civil aircraft.