SEARCH · Engineering Papers

Results for “multi-level algorithms”

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 37 records · Page 2

All sources NASA NTRS DOE OSTI

NASA NTRS1997

On the Multilevel Solution Algorithm for Markov Chains

We discuss the recently introduced multilevel algorithm for the steady-state solution of Markov chains. The method is based on an aggregation principle which is well established in the literature and features a multiplicative coarse-level correction. Recursive application of the aggregation principle, which uses an operator-dependent coarsening, yields a multi-level method which has been shown experimentally to give results significantly faster than the typical methods currently in use. When cast as a multigrid-like method, the algorithm is seen to be a Galerkin-Full Approximation Scheme with a solution-dependent prolongation operator. Special properties of this prolongation lead to the cancellation of the computationally intensive terms of the coarse-level equations.

Horton, Graham↗

NASA NTRS1997

Progress in Parallel Schur Complement Preconditioning for Computational Fluid Dynamics

We consider preconditioning methods for nonself-adjoint advective-diffusive systems based on a non-overlapping Schur complement procedure for arbitrary triangulated domains. The ultimate goal of this research is to develop scalable preconditioning algorithms for fluid flow discretizations on parallel computing architectures. In our implementation of the Schur complement preconditioning technique, the triangulation is first partitioned into a number of subdomains using the METIS multi-level k-way partitioning code. This partitioning induces a natural 2X2 partitioning of the p.d.e. discretization matrix. By considering various inverse approximations of the 2X2 system, we have developed a family of robust preconditioning techniques. A computer code based on these ideas has been developed and tested on the IBM SP2 and the SGI Power Challenge array using MPI message passing protocol. A number of example CFD calculations will be presented to illustrate and assess various Schur complement approximations.

Barth, Timothy J.↗

NASA NTRS1990

New multi-level codes over GF(q)

Set partitioning to multi-dimensional signal spaces over GF(q), particularly GF sup q-1(q) and GF sup q (q), and show how to construct both multi-level block codes and multi-level trellis codes over GF(q). Two classes of multi-level (n, k, d) block codes over GF(q) with block length n, number of information symbols k, and minimum distance d sub min greater than or = d, are presented. These two classes of codes use Reed-Solomon codes as component codes. They can be easily decoded as block length q-1 Reed-Solomon codes or block length q or q + 1 extended Reed-Solomon codes using multi-stage decoding. Many of these codes have larger distances than comparable q-ary block codes, as component codes. Low rate q-ary convolutional codes, work error correcting convolutional codes, and binary-to-q-ary convolutional codes can also be used to construct multi-level trellis codes over GF(q) or binary-to-q-ary trellis codes, some of which have better performance than the above block codes. All of the new codes have simple decoding algorithms based on hard decision multi-stage decoding.

Wu, Jiantian↗

NASA NTRS1992

New multilevel codes over GF(q)

Wu, Jiantian↗

NASA NTRS1988

Flight test results of a vector-based failure detection and isolation algorithm for a redundant strapdown inertial measurement unit

Flight test results of a vector-based fault-tolerant algorithm for a redundant strapdown inertial measurement unit are presented. Because the inertial sensors provide flight-critical information for flight control and navigation, failure detection and isolation is developed in terms of a multi-level structure. Threshold compensation techniques for gyros and accelerometers, developed to enhance the sensitivity of the failure detection process to low-level failures, are presented. Four flight tests, conducted in a commercial transport type environment, were used to determine the ability of the failure detection and isolation algorithm to detect failure signals, such a hard-over, null, or bias shifts. The algorithm provided timely detection and correct isolation of flight control- and low-level failures. The flight tests of the vector-based algorithm demonstrated its capability to provide false alarm free dual fail-operational performance for the skewed array of inertial sensors.

Morrell, F. R.↗

NASA NTRS1999

The Design of a Fault-Tolerant COTS-Based Bus Architecture

In this paper, we report our experiences and findings on the design of a fault-tolerant bus architecture comprised of two COTS buses, the IEEE 1394 and the 12C. This fault-tolerant bus is the backbone system bus for the avionics architecture of the X2000 program at the Jet Propulsion Laboratory. COTS buses are attractive because of the availability of low cost commercial products. However, they are not specifically designed for highly reliable applications such as long-life deep-space missions. The X2000 design team has devised a multi-level fault tolerance approach to compensate for this shortcoming of COTS buses. First, the approach enhances the fault tolerance capabilities of the IEEE 1394 and 12 C buses by adding a layer of fault handling hardware and software. Second, algorithms are developed to enable the IEEE 1394 and the 12 C buses assist each other to isolate and recovery from faults. Third, the set of IEEE 1394 and 12 C buses is duplicated to further enhance system reliability. The X2000 design team has paid special attention to guarantee that all fault tolerance provisions will not cause the bus design to deviate from the commercial standard specifications. Otherwise, the economic attractiveness of using COTS will be diminished. The hardware and software design of the X2000 fault-tolerant bus are being implemented and flight hardware will be delivered to the ST4 and Europa Orbiter missions.

Chau, Savio N.↗

NASA NTRS1987

Sensitivity method for integrated structure/active control law design

The development is described of an integrated structure/active control law design methodology for aeroelastic aircraft applications. A short motivating introduction to aeroservoelasticity is given along with the need for integrated structures/controls design algorithms. Three alternative approaches to development of an integrated design method are briefly discussed with regards to complexity, coordination and tradeoff strategies, and the nature of the resulting solutions. This leads to the formulation of the proposed approach which is based on the concepts of sensitivity of optimum solutions and multi-level decompositions. The concept of sensitivity of optimum is explained in more detail and compared with traditional sensitivity concepts of classical control theory. The analytical sensitivity expressions for the solution of the linear, quadratic cost, Gaussian (LQG) control problem are summarized in terms of the linear regulator solution and the Kalman Filter solution. Numerical results for a state space aeroelastic model of the DAST ARW-II vehicle are given, showing the changes in aircraft responses to variations of a structural parameter, in this case first wing bending natural frequency.

Gilbert, Michael G.↗

DOE OSTI2026

Linear complexity

We present factorization and solution phases for a new linear complexity direct solver designed for concurrent batch operations on fine-grained parallel architectures, for matrices amenable to hierarchical representation. We focus on the strong-admissibility-based $\mathscr{H}^{2}$ format, where strong recursive skeletonization factorization compresses remote interactions. We build upon previous implementations of $\mathscr{H}^{2}$ matrix construction for efficient factorization and solution algorithm design, which are illustrated graphically in stepwise detail. The algorithms are ‘blackbox’ in the sense that the only inputs are the matrix and right-hand side, without analytical or geometrical information about the origin of the system. We demonstrate linear complexity scaling in both time and memory on four representative families of dense matrices up to one million in size. Parallel scaling up to 16 threads is enabled by a multi-level matrix graph coloring and avoidance of dynamic memory allocations thanks to prefix-sum memory management. An experimental backward error analysis is included. We break down the timings of different phases, identify phases that are memory-bandwidth limited, and discuss alternatives for phases that may be sensitive to the trend to employ lower precisions for performance.

Boukaram, Wajih↗

NASA NTRS1993

A comparison of locally adaptive multigrid methods: LDC, FAC and FIC

This study is devoted to a comparative analysis of three 'Adaptive ZOOM' (ZOom Overlapping Multi-level) methods based on similar concepts of hierarchical multigrid local refinement: LDC (Local Defect Correction), FAC (Fast Adaptive Composite), and FIC (Flux Interface Correction)--which we proposed recently. These methods are tested on two examples of a bidimensional elliptic problem. We compare, for V-cycle procedures, the asymptotic evolution of the global error evaluated by discrete norms, the corresponding local errors, and the convergence rates of these algorithms.

Khadra, Khodor↗

DOE OSTI2025

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-based approaches often have delays that are too long to be applied in practice. It is paramount to have systems with extremely low delays to quickly and with high fidelity adjust quantum hardware settings, where fidelity is defined as overlap with a target quantum state. Here, we utilize machine learning (ML) models to determine control-pulse parameters for preparing Selective Number-dependent Arbitrary Phase (SNAP) gates in microwave cavity qudits, which are multi-level quantum systems that serve as elementary computation units for quantum computing. The methodology involves data generation using classical optimization techniques, ML model development, design space exploration, and quantization for hardware implementation. Our results demonstrate the efficacy of the proposed approach, with optimized models achieving low gate trace infidelity near $10^{-3}$ and efficient utilization of programmable logic resources.

Sanders, Flor [Columbia U.]↗

DOE OSTI2025

Faster solutions to the interdiction defense problem using suboptimal solutions

The interdiction defense (ID) problem solves a defender-attacker-defender model where the defender and attacker share the same set of components to harden and target. Here, we build upon the best response intersection (BRI) algorithm by developing the BRI with suboptimal solutions (BRI-SS) algorithm to solve the ID problem. The BRI-SS algorithm utilizes off-the-shelf optimization solvers that return suboptimal solutions at no additional computation cost. We derive novel cuts from suboptimal solutions, reducing the number of iterations required for the algorithm to converge while maintaining optimality guarantees. We also present a heuristic that utilizes all obtained suboptimal solutions to select the next defense to evaluate at each iteration. We perform computational experiments applied to power grid interdiction on standard test cases. Our results demonstrate that the BRI-SS algorithm consistently outperforms the BRI algorithm across all test cases.

Computer science↗

NASA NTRS2000

Performance of the OVERFLOW-MLP and LAURA-MLP CFD Codes on the NASA Ames 512 CPU Origin System

The shared memory Multi-Level Parallelism (MLP) technique, developed last year at NASA Ames has been very successful in dramatically improving the performance of important NASA CFD codes. This new and very simple parallel programming technique was first inserted into the OVERFLOW production CFD code in FY 1998. The OVERFLOW-MLP code's parallel performance scaled linearly to 256 CPUs on the NASA Ames 256 CPU Origin 2000 system (steger). Overall performance exceeded 20.1 GFLOP/s, or about 4.5x the performance of a dedicated 16 CPU C90 system. All of this was achieved without any major modification to the original vector based code. The OVERFLOW-MLP code is now in production on the inhouse Origin systems as well as being used offsite at commercial aerospace companies. Partially as a result of this work, NASA Ames has purchased a new 512 CPU Origin 2000 system to further test the limits of parallel performance for NASA codes of interest. This paper presents the performance obtained from the latest optimization efforts on this machine for the LAURA-MLP and OVERFLOW-MLP codes. The Langley Aerothermodynamics Upwind Relaxation Algorithm (LAURA) code is a key simulation tool in the development of the next generation shuttle, interplanetary reentry vehicles, and nearly all "X" plane development. This code sustains about 4-5 GFLOP/s on a dedicated 16 CPU C90. At this rate, expected workloads would require over 100 C90 CPU years of computing over the next few calendar years. It is not feasible to expect that this would be affordable or available to the user community. Dramatic performance gains on cheaper systems are needed. This code is expected to be perhaps the largest consumer of NASA Ames compute cycles per run in the coming year.The OVERFLOW CFD code is extensively used in the government and commercial aerospace communities to evaluate new aircraft designs. It is one of the largest consumers of NASA supercomputing cycles and large simulations of highly resolved full aircraft are routinely undertaken. Typical large problems might require 100s of Cray C90 CPU hours to complete. The dramatic performance gains with the 256 CPU steger system are exciting. Obtaining results in hours instead of months is revolutionizing the way in which aircraft manufacturers are looking at future aircraft simulation work. Figure 2 below is a current state of the art plot of OVERFLOW-MLP performance on the 512 CPU Lomax system. As can be seen, the chart indicates that OVERFLOW-MLP continues to scale linearly with CPU count up to 512 CPUs on a large 35 million point full aircraft RANS simulation. At this point performance is such that a fully converged simulation of 2500 time steps is completed in less than 2 hours of elapsed time. Further work over the next few weeks will improve the performance of this code even further.The LAURA code has been converted to the MLP format as well. This code is currently being optimized for the 512 CPU system. Performance statistics indicate that the goal of 100 GFLOP/s will be achieved by year's end. This amounts to 20x the 16 CPU C90 result and strongly demonstrates the viability of the new parallel systems rapidly solving very large simulations in a production environment.

Taft, James R.↗

DOE OSTI2026

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗

DOE OSTI2025

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗

NASA NTRS1986

Numerical difficulties associated with using equality constraints to achieve multi-level decomposition in structural optimization

There has been recent interest in multidisciplinary multilevel optimization applied to large engineering systems. The usual approach is to divide the system into a hierarchy of subsystems with ever increasing detail in the analysis focus. Equality constraints are usually placed on various design quantities at every successive level to ensure consistency between levels. In many previous applications these equality constraints were eliminated by reducing the number of design variables. In complex systems this may not be possible and these equality constraints may have to be retained in the optimization process. In this paper the impact of such a retention is examined for a simple portal frame problem. It is shown that the equality constraints introduce numerical difficulties, and that the numerical solution becomes very sensitive to optimization parameters for a wide range of optimization algorithms.

Thareja, R.↗

NASA NTRS1992

Least Reliable Bits Coding (LRBC) for high data rate satellite communications

An analysis and discussion of a bandwidth efficient multi-level/multi-stage block coded modulation technique called Least Reliable Bits Coding (LRBC) is presented. LRBC uses simple multi-level component codes that provide increased error protection on increasingly unreliable modulated bits in order to maintain an overall high code rate that increases spectral efficiency. Further, soft-decision multi-stage decoding is used to make decisions on unprotected bits through corrections made on more protected bits. Using analytical expressions and tight performance bounds it is shown that LRBC can achieve increased spectral efficiency and maintain equivalent or better power efficiency compared to that of Binary Phase Shift Keying (BPSK). Bit error rates (BER) vs. channel bit energy with Additive White Gaussian Noise (AWGN) are given for a set of LRB Reed-Solomon (RS) encoded 8PSK modulation formats with an ensemble rate of 8/9. All formats exhibit a spectral efficiency of 2.67 = (log2(8))(8/9) information bps/Hz. Bit by bit coded and uncoded error probabilities with soft-decision information are determined. These are traded with with code rate to determine parameters that achieve good performance. The relative simplicity of Galois field algebra vs. the Viterbi algorithm and the availability of high speed commercial Very Large Scale Integration (VLSI) for block codes indicates that LRBC using block codes is a desirable method for high data rate implementations.

Vanderaar, Mark↗

NASA NTRS1990

NOVA: A new multi-level logic simulator

A new logic simulator that was developed at the NASA Space Engineering Research Center for VLSI Design was described. The simulator is multi-level, being able to simulate from the switch level through the functional model level. NOVA is currently in the Beta test phase and was used to simulate chips designed for the NASA Space Station and the Explorer missions. A new algorithm was devised to simulate bi-directional pass transistors and a preliminary version of the algorithm is presented. The usage of functional models in NOVA is also described and performance figures are presented.

Miles, L.↗

NASA NTRS1995

Investigation of biomass burning and aerosol loading and transport in South America utilizing geostationary satellites

This study attempts to assess the extent of burning and associated aerosol transport regimes in South America and the South Atlantic using geostationary satellite observations, in order to explore the possible roles of biomass burning in climate change and more directly in atmospheric chemistry and radiative transfer processes. Modeling and analysis efforts have suggested that the direct and indirect radiative effects of aerosols from biomass burning may play a major role in the radiative balance of the earth and are an important factor in climate change calculations. One of the most active regions of biomass burning is located in South America, associated with deforestation in the selva (forest), grassland management, and other agricultural practices. As part of the NASA Aerosol Interdisciplinary Program, we are utilizing GOES-7 (1988) and GOES-8 (1995) visible and multispectral infrared data (4, 11, and 12 microns) to document daily biomass burning activity in South America and to distinguish smoke/aerosols from other multi-level clouds and low-level moisture. This study catalogues the areal extent and transport of smoke/aerosols throughout the region and over the Atlantic Ocean for the 1988 (July-September) and 1995 (June-October) biomass burning seasons. The smoke/haze cover estimates are compared to the locations of fires to determine the source and verify the haze is actually associated with biomass burning activities. The temporal resolution of the GOES data (half-hourly in South America) makes it possible to determine the prevailing circulation and transport of aerosols by considering a series of visible and infrared images and tracking the motion of smoke, haze and adjacent clouds. The study area extends from 40 to 70 deg W and 0 to 40 deg S with aerosol coverage extending over the Atlantic Ocean when necessary. Fire activity is estimated with the GOES Automated Biomass Burning Algorithm (ABBA). To date, our efforts have focused on GOES-7 and GOES-8 ABBA development, algorithm development for aerosol monitoring, data acquisition and archiving, and participation in the SCAR-C and SCAR-B field programs which have provided valuable information for algorithm testing and validation. Implementation of the initial version of the GEOS-8 ABBA on case studies in North, Central, and South America has demonstrated the improved capability for monitoring diurnal fire activity and smoke/aerosol transport with the GOES-8 throughout the Western Hemisphere.

Menzel, Paul↗