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At least 1,027 records · Page 57

Space Launch System Scale Model Acoustic Test Ignition Overpressure Testing

The overpressure phenomenon is a transient fluid dynamic event occurring during rocket propulsion system ignition. This phenomenon results from fluid compression of the accelerating plume gas, subsequent rarefaction, and subsequent propagation from the exhaust trench and duct holes. The high-amplitude unsteady fluid-dynamic perturbations can adversely affect the vehicle and surrounding structure. Commonly known as ignition overpressure (IOP), this is an important design-to environment for the Space Launch System (SLS) that NASA is currently developing. Subscale testing is useful in validating and verifying the IOP environment. This was one of the objectives of the Scale Model Acoustic Test, conducted at Marshall Space Flight Center. The test data quantifies the effectiveness of the SLS IOP suppression system and improves the analytical models used to predict the SLS IOP environments. The reduction and analysis of the data gathered during the SMAT IOP test series requires identification and characterization of multiple dynamic events and scaling of the event waveforms to provide the most accurate comparisons to determine the effectiveness of the IOP suppression systems. The identification and characterization of the overpressure events, the waveform scaling, the computation of the IOP suppression system knockdown factors, and preliminary comparisons to the analytical models are discussed.

Nance, Donald↗

Pele: An Exascale-Ready Suite of Combustion Codes

High fidelity simulations of realistic combustion devices are extremely demanding computationally because of the requirements to capture complex fuel chemical decomposition, its intricate interactions with turbulent, often multiphase, flows, and the wide separation of space and time scales between the thin flame and the device boundaries. Software required to carry out such computations tends to be extremely complex, particularly when designed to exploit hardware accelerators, and can be difficult to port and maintain. We present Pele, a performance portable suite of tools for the simulation of combustion systems, including codes to evolve reactive multiphase configurations in the low Mach number and compressible flow regimes, along with a set of inter-compatible post processing and in situ analysis tools. The Pele suite of tools is built on top of the AMReX framework for block-structured adaptive mesh refinement, which provides efficient data structures and algorithms that enable the development of a wide variety of efficient mesh and particle based PDE integration schemes. A hierarchical MPI+X parallelism scheme supports CPU-only and accelerated architectures, where X can be OpenMP, CUDA, and HIP based approaches for intra-node computational work distribution. The algorithms and data structures underlying the Pele simulation and analysis tools are highly scalable and performant across a wide variety of high-performance computing platforms, including DOEs newest exascale-class machines, Frontier and Aurora. The simulation and analysis tools are fully documented and freely distributed as open source via GitHub. We present key algorithmic and software challenges, solution strategies, performance and resulting set of capabilities.

AMReX↗

Comparison of Analysis with Test for Static Loading of Two Hypersonic Inflatable Aerodynamic Decelerator Concepts

Acceptance of new spacecraft structural architectures and concepts requires validated design methods to minimize the expense involved with technology demonstration via flight-testing. Hypersonic Inflatable Aerodynamic Decelerator (HIAD) architectures are attractive for spacecraft deceleration because they are lightweight, store compactly, and utilize the atmosphere to decelerate a spacecraft during entry. However, designers are hesitant to include these inflatable approaches for large payloads or spacecraft because of the lack of flight validation. This publication summarizes results comparing analytical results with test data for two concepts subjected to representative entry, static loading. The level of agreement and ability to predict the load distribution is considered sufficient to enable analytical predictions to be used in the design process.

Lyle, Karen H.↗

SOHO Ultraviolet Coronagraph Spectrometer (UVCS) Mission Operations and Data Analysis

The scientific goal of UVCS is to obtain detailed empirical descriptions of the extended solar corona as it evolves over the solar cycle and to use these descriptions to identify and understand the physical processes responsible for coronal heating, solar wind acceleration, coronal mass ejections (CMEs), and the phenomena that establish the plasma properties of the solar wind as measured by 'in situ' solar wind instruments. This report covers the period from 01 February 2002 to 15 February 2003. During that time, UVCS observations have consisted of three types: 1) standard synoptic observations comprising, primarily, the H I Ly alpha line profile and the O VI 103.2 and 103.7 nm intensity over a range of heights from 1.5 to about 3.0 solar radii and covering 360 degrees about the sun, 2) sit and stare watches for CMEs, and 3) special observations designed by the UVCS Lead Observer of the Week for a specific scientific purpose. The special observations are often coordinated with those of other space-based and ground-based instruments and they often are part of SOHO joint observation programs and campaigns. Lead observers have included UVCS Co-Investigators, scientists from the solar physics community and several graduate and undergraduate level students. UVCS has continued to achieve its purpose of using powerful spectroscopic diagnostic techniques to obtain a much more detailed description of coronal structures and dynamic phenomena than existed before the SOHO mission. The new descriptions of coronal mass ejections (CMEs) and coronal structures from UVCS have inspired a large number of theoretical studies aimed at identifying the physical processes responsible for CMEs and solar wind acceleration in coronal holes and streamers. UVCS has proven to be a very stable instrument. Stellar observations have demonstrated its stability. UVCS has required no flight software modifications and all mechanisms are operational. The UVCS O VI Channel with its redundant optical path for wavelengths near H I Ly alpha is capable of observing the entire UVCS wavelength range. Since December 1998, the O VI Channel has been used for all UVCS observations. Although the H I Ly alpha Channel and detector are still operational, increases in the dark count up to about 5 x 10(exp -4) counts/sec/pixel and an increase in high voltage current to within a factor of two of the maximum used in the laboratory before flight led to the decision to not use that detector at the present time. There is no significant decrease in the scientific capability of UVCS owing to the O VI channel redundant optical path. UVCS data, data analysis software, calibration files and the mission log are available from the SOHO archive and SAO. All UVCS data is now available to scientists and the general public via the SOHO Data Archive and SAO within three months of the observations. UVCS has resulted in 46 scientific papers in 2002. There were numerous presentations at scientific meetings. All requests for observation time by qualified outside users have been granted.

Kohl, John L.↗

Quantification and evaluation of strain reduction from small-bubble gas injection in Spallation Neutron Source target vessels

Small-bubble gas injection has been routinely utilized in the operation of Spallation Neutron Source (SNS) mercury targets since 2017 to mitigate cavitation-induced erosion damage to target vessels. Strain measurements of target vessels collected in-situ during initial operation with gas injection were used to study the gas injection effect on the structural response of targets to proton pulses. A significant strain reduction owing to gas injection was found by comparing the strain measurement data during operation with and without gas injection. The research presented here focuses on quantifying strain reductions in SNS targets and evaluating the effect of small-bubble gas injection by comparing different bubbler types and target designs. The strain measurement results show the gas injection significantly reduced strain in SNS target vessels; strain values decreased by 30% to 80% for targets operating with gas injection. Stress and strain responses of SNS targets were simulated to numerically evaluate the gas injection effect. Based on the predicted stresses with and without gas injection, the fatigue lifetimes of SNS jet-flow design target were estimated using fe-safe fatigue analysis software. The simulations show these reductions should improve the fatigue life of target vessels and allow SNS targets to meet their fatigue design goal.

Fatigue life estimation↗

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was implemented to offer an efficient framework for determining material characteristics from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enable parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM). SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography or other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

The Porous Microstructure Analysis (PuMA) software

The open-source Porous Microstructure Analysis (PuMA) software was created to offer an efficient framework for determining material properties from 3D microstructures. Its development was inspired by progress in X-ray microtomography, an imaging technology that captures the internal structure of materials in 3D, and even in a 4D temporal context. Over recent years, this method has transformed the domain of materials science due to its capability to non-destructively examine material microstructures while presenting digital data about their geometrical details. It has provided insights into materials relevant to several NASA missions, including heatshields, parachute fabrics, meteorites, and other advanced composites. PuMA, in its current version 3, delivers an array of features, spanning from basic geometric insights of a microstructure to intricate anisotropic thermo-elastic and chemical behavior. Specifically, the software evaluates morphological attributes (specific surface area, volume fractions, mean intercept lengths, orientation) and physical characteristics (conductivity, elasticity, permeability, and tortuosity). Additionally, it can model material degradation processes, such as oxidation and surface chemistry interactions. The software can generate synthetic microstructures, from straightforward geometrical designs to intricate woven and non-woven geometries. Coupling material generation and characterization enables parametric studies and sensitivity analysis to optimize the microstructural performance and inform design decisions and reliability assessment based on uncertainty quantification. A recent addition to PuMA includes the TomoSAM plugin, devised to incorporate the cutting-edge Segment Anything Model (SAM) into our image segmentation workflow. SAM is a promptable deep learning model that can identify objects and create image masks in a zero-shot manner, based only on a few user clicks. The synergy between these tools aids in the segmentation of complex 3D datasets from tomography and other imaging techniques, which would otherwise require a laborious manual segmentation process.

Tomography↗

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗

The microbiologist's guide to metaproteomics

Metaproteomics is an emerging approach for studying microbiomes, offering the ability to characterize proteins that underpin microbial functionality within diverse ecosystems. As the primary catalytic and structural components of microbiomes, proteins provide unique insights into the active processes and ecological roles of microbial communities. By integrating metaproteomics with other omics disciplines, researchers can gain a comprehensive understanding of microbial ecology, interactions, and functional dynamics. This review, developed by the Metaproteomics Initiative (www.metaproteomics.org), serves as a practical guide for both microbiome and proteomics researchers, presenting key principles, state-of-the-art methodologies, and analytical workflows essential to metaproteomics. Topics covered include experimental design, sample preparation, mass spectrometry techniques, data analysis strategies, and statistical approaches.

bioinformatics↗

Fundamental electronic structure and multiatomic bonding in 13 biocompatible high-entropy alloys

High-entropy alloys (HEAs) have attracted great attention due to their many unique properties and potential applications. The nature of interatomic interactions in this unique class of complex multicomponent alloys is not fully developed or understood. We report a theoretical modeling technique to enable in-depth analysis of their electronic structures and interatomic bonding, and predict HEA properties based on the use of the quantum mechanical metrics, the total bond order density (TBOD) and the partial bond order density (PBOD). Application to 13 biocompatible multicomponent HEAs yields many new and insightful results, including the inadequacy of using the valence electron count, quantification of large lattice distortion, validation of mechanical properties with experiment data, modeling porosity to reduce Young’s modulus. This work outlines a road map for the rational design of HEAs for biomedical applications.

36 MATERIALS SCIENCE↗

Update of Erosion Conditions and Assessment of Mitigation Options for the L-Bar Site

The L-Bar former uranium milling site was remediated and closed per regulations and is now under the long-term stewardship of the U.S. Department of Energy, Office of Legacy Management (DOE/LM). Since assuming stewardship in 2004, DOE/LM has observed erosion and sedimentation processes at the L-Bar Site that will challenge meeting the design closure criteria in the long term, and therefore erosion control structures were installed in several areas. Portions of these structures were subsequently damaged by summer convective storm events and they are being redesigned. At the request of DOE/LM, Desert Research Institute (DRI) reviewed the proposed redesign plans of the erosion control structures. The purpose of this review is to support DOE/LM decisions regarding mitigation of ongoing erosion processes, including assessing possible repair of the existing erosion control structures, as well as plan for effective long-term site management. This design review is performed in reference to the Uranium Mill Tailings Radiation Control Act (UMTRCA) standards contained in 40 CFR 192.02 that require containment of residual radioactive material be effective for up to 1,000 years (if achievable, but certainly for 200 years), limit radon release, protect groundwater, and minimize future maintenance. The erosion control structures under review are not subject to the UMTRCA standard directly, but they contribute to the performance of the overall containment system by virtue of their relationship with the large diversion channels bounding the disposal cell. The 11 design drawings included in “Erosion Control Alternatives Analysis, L-Bar, New Mexico, Disposal Site, LTS-111-0043-08-002,” dated January 11, 2019, and listed in Appendix A, and supporting calculations in Weston (2019) are the focus of the review. Additionally, DOE/LM provided supporting data such as a 2018 photogrammetry-based digital elevation model of the site, precipitation records collected from an on-site weather station, and sedimentation records collected at an on-site basin. This assessment includes review of the proposed design to mitigate current site conditions but also addresses site changes between the initial erosion assessment report (Miller et al., 2012) and current conditions. The analysis is at a predesign engineering level and does not include development of hydraulic or sediment transport models. Site precipitation data are included in Miller et al. (2012). The natural conditions of the site, the design of site diversion systems, observed erosion at the site, and predesign engineering analysis are used to develop a holistic view of the challenges to L-Bar Site stability and possible responsive actions.

54 ENVIRONMENTAL SCIENCES↗

On the utilization of engineering knowledge in design optimization

Some current research work conducted at the University of Michigan is described to illustrate efforts for incorporating knowledge in optimization in a nontraditional way. The incorporation of available knowledge in a logic structure is examined in two circumstances. The first examines the possibility of introducing global design information in a local active set strategy implemented during the iterations of projection-type algorithms for nonlinearly constrained problems. The technique used algorithms for nonlinearly constrained problems. The technique used combines global and local monotinicity analysis of the objective and constraint functions. The second examines a knowledge-based program which aids the user to create condigurations that are most desirable from the manufacturing assembly viewpoint. The data bank used is the classification scheme suggested by Boothroyd. The important aspect of this program is that it is an aid for synthesis intended for use in the design concept phase in a way similar to the so-called idea-triggers in creativity-enhancement techniques like brain-storming. The idea generation, however, is not random but it is driven by the goal of achieving the best acceptable configuration.

Papalambros, P.↗

TRMM Common Microphysics Products: A Tool for Evaluating Spaceborne Precipitation Retrieval Algorithms

A customized product for analysis of microphysics data collected from aircraft during field campaigns in support of the TRMM program is described. These Common Microphysics Products (CMP's) are designed to aid in evaluation of TRMM spaceborne precipitation retrieval algorithms. Information needed for this purpose (e.g., particle size spectra and habit, liquid and ice water content) was derived using a common processing strategy on the wide variety of microphysical instruments and raw native data formats employed in the field campaigns. The CMP's are organized into an ASCII structure to allow easy access to the data for those less familiar with and without the tools to accomplish microphysical data processing. Detailed examples of the CMP show its potential and some of its limitations. This approach may be a first step toward developing a generalized microphysics format and an associated community-oriented, non-proprietary software package for microphysics data processing, initiatives that would likely broaden community access to and use of microphysics datasets.

Kingsmill, David E.↗

Computational synthesis of a new generation of 2D-based perovskite quantum materials

Perovskite-based optoelectronic devices have emerged as a promising energy source due to their potential for scalable production. This study introduces “perovskene,” a novel class of 2D materials derived from the ABC3-like perovskites, synthesized via a data-driven, high-throughput computational strategy. We harness machine learning and multitarget deep neural networks to systematically investigate the structure–property relations, paving the way for targeted material design and optimization in fields such as renewable energy, electronics, and catalysis. The characterization of over 1500 synthesized structures shows that more than 500 structures are stable, revealing properties such as ultra-low work function and large magnetic moment, underscoring the potential for advanced technological applications.

2D materials↗

Experimental design of a W-band corrugated waveguide for wakefield acceleration studies

Radiofrequency (RF) structures in the sub-terahertz (sub-THz) regime are of interest for applications in structure wakefield acceleration due to their compact size and potential for high gradients. Here, we present the design, fabrication, and experimental setup of a metallic corrugated waveguide at 110 GHz, optimized for the 42 MeV electron beam parameters at the Argonne Wakefield Accelerator (AWA). The emittance exchange (EEX) beamline at AWA was used to perform longitudinal bunch shaping for two cases: (1) a high decelerating gradient experienced by a single drive electron bunch about 250 μm long; (2) a high transformer ratio using a two-bunch train consisting of a triangularly shaped drive bunch followed by a long witness bunch to probe the wakefield. Preliminary experimental results are presented, and data analysis is ongoing.

43 PARTICLE ACCELERATORS↗

Developing Procedures to Implement Geometric Imperfections Beyond Right Circular Cylindrical Shells in Finite Element Method Models

Analysis of aerospace structures is frequently conducted using nominal dimensions and frequently assumes ideal conditions in loading, contact, constraints, et cetera. Off-nominal dimensions and nonideal conditions, however, are present in all structures. These are the result of widely ranging causes from coefficient of thermal expansion mismatches, manufacturing tooling anomalies, to assembly procedures that inadvertently alter the structure. Specifically, geometric imperfections can have potentially significant influence on the response of a structural test article observed in an experiment versus the response given by a numerical simulation. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS) was previously presented as a set of Python scripts to calculate and implement as-manufactured geometric midsurface and thickness imperfections into finite element method (FEM) shell models of nominally right circular cylinders. By taking advantage of the simple shape of a right circular cylinder, interpolations of the measured data points were able to be performed along directions that aligned to the cylindrical coordinate system axes of the entire structure. By taking advantage of the shell representation of the real structure as opposed to modeling using a continuum representation, the thickness variation was able to be implemented by shell section definitions instead of having to modify the position of multiple nodes in the thickness direction. Py_TIGIRS is a useful tool that established a procedural example on how to implement geometric imperfections in right circular cylindrical shell structures. Three new procedures, each expanded from concepts established in Py_TIGIRS, are proposed for various test-article designs and are intended to broaden the range of structures that can be modeled with measured geometric imperfections in the structural analysis community. Each test-article design introduces new challenges to successfully implement geometric imperfections into a FEM model. The first test-article design consists of a carbon fiber reinforced polymer square plate with a hat-shaped stiffener co-cured on one side. This test-article design was for a novel seven-point bend test that was also previously presented. Manufacturing and cure-cycle imperfections are observed using digital image correlation (DIC) techniques. As thermal expansion coefficient mismatches between the plate and stiffener materials were anticipated, a thermal analysis study with continuum shell and solid elements was conducted to capture the global shape observed prior to testing. The second test-article design is of a similar hat-stiffened plate configuration, but with a side length ratio near 3:1 with elongation in the stiffener direction. The test article was used to characterize the response to uniaxial compressive loading in the direction of the stiffener. Due to differing manufacturing steps, a thermal analysis like the one developed for the seven-point bend configuration was unable to mimic the observed geometric imperfections. Instead, a strategy based on applying deformations directly to the structure during analysis was developed for continuum shell and solid element representation of a stiffened panel.

Geometric imperfections↗

Developing a MATLAB(registered)-Based Tool for Visualization and Transformation

An important step in the structural design and development of spacecraft is the experimental identification of a structure s modal characteristics, such as its natural frequencies and modes of vibration. These characteristics are vital to developing a representative model of any given structure or analyzing the range of input frequencies that can be handled by a particular structure. When setting up such a representative model of a structure, careful measurements using precision equipment (such as accelerometers and instrumented hammers) must be made on many individual points of the structure in question. The coordinate location of each data point is used to construct a wireframe geometric model of the structure. Response measurements obtained from the accelerometers is used to generate the modal shapes of the particular structure. Graphically, this is displayed as a combination of the ways a structure will ideally respond to a specified force input. Two types of models of the tested structure are often used in modal analysis: an analytic model showing expected behavior of the structure, and an experimental model showing measured results due to observed phenomena. To evaluate the results from the experimental model, a comparison of analytic and experimental results must be made between the two models. However, comparisons between these two models become difficult when the two coordinate orientations differ in a manner such that results are displayed in an unclear fashion. Such a problem proposes the need for a tool that not only communicates a graphical image of a structure s wireframe geometry based on various measurement locations (called nodes), but also allows for a type of transformation of the image s coordinate geometry so that a model s coordinate orientation is made to match the orientation of another model. Such a tool should also be designed so that it is able to construct coordinate geometry based on many different listings of node locations and is able to transform the wireframe coordinate orientation to match almost any possible orientation (i.e. it should not be a problem specific application) if it is to be of much value in modal analysis. Also, since universal files are used to store modal parameters and wireframe geometry, the tool must be able to read and extract information from universal files and use these files to exchange model data.The purpose of this project is to develop such a tool as a computer graphical user interface (GUI) capable of performing the following tasks: 1) Browsing for a particular universal file within the computer directory and displaying the name of this file to the screen; 2) Plotting each of the nodes within the universal file in a useful, descriptive, and easily understood figure; 3) Reading the node numbers from the selected file and listing these node numbers to the user for selection in an easily accessible format; 4) Allowing for user selection of a new model orientation defined by three selected nodes; and 5) Allowing the user to specify a directory to which the transformed model s node locations will be saved, and saving the transformed node locations to the specified file.

Anderton, Blake J.↗

Numerical Propulsion System Simulation: An Overview

The cost of implementing new technology in aerospace propulsion systems is becoming prohibitively expensive and time consuming. One of the main contributors to the high cost and lengthy time is the need to perform many large-scale hardware tests and the inability to integrate all appropriate subsystems early in the design process. The NASA Glenn Research Center is developing the technologies required to enable simulations of full aerospace propulsion systems in sufficient detail to resolve critical design issues early in the design process before hardware is built. This concept, called the Numerical Propulsion System Simulation (NPSS), is focused on the integration of multiple disciplines such as aerodynamics, structures and heat transfer with computing and communication technologies to capture complex physical processes in a timely and cost-effective manner. The vision for NPSS, as illustrated, is to be a "numerical test cell" that enables full engine simulation overnight on cost-effective computing platforms. There are several key elements within NPSS that are required to achieve this capability: 1) clear data interfaces through the development and/or use of data exchange standards, 2) modular and flexible program construction through the use of object-oriented programming, 3) integrated multiple fidelity analysis (zooming) techniques that capture the appropriate physics at the appropriate fidelity for the engine systems, 4) multidisciplinary coupling techniques and finally 5) high performance parallel and distributed computing. The current state of development in these five area focuses on air breathing gas turbine engines and is reported in this paper. However, many of the technologies are generic and can be readily applied to rocket based systems and combined cycles currently being considered for low-cost access-to-space applications. Recent accomplishments include: (1) the development of an industry-standard engine cycle analysis program and plug 'n play architecture, called NPSS Version 1, (2) A full engine simulation that combines a 3D low-pressure subsystem with a 0D high pressure core simulation. This demonstrates the ability to integrate analyses at different levels of detail and to aerodynamically couple components, the fan/booster and low-pressure turbine, through a 3D computational fluid dynamics simulation. (3) Simulation of all of the turbomachinery in a modern turbofan engine on parallel computing platform for rapid and cost-effective execution. This capability can also be used to generate full compressor map, requiring both design and off-design simulation. (4) Three levels of coupling characterize the multidisciplinary analysis under NPSS: loosely coupled, process coupled and tightly coupled. The loosely coupled and process coupled approaches require a common geometry definition to link CAD to analysis tools. The tightly coupled approach is currently validating the use of arbitrary Lagrangian/Eulerian formulation for rotating turbomachinery. The validation includes both centrifugal and axial compression systems. The results of the validation will be reported in the paper. (5) The demonstration of significant computing cost/performance reduction for turbine engine applications using PC clusters. The NPSS Project is supported under the NASA High Performance Computing and Communications Program.

Lytle, John K.↗