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Results for “problem solving complexity”

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.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Data-Driven Learning for the Mori--Zwanzig Formalism: A Generalization of the Koopman Learning Framework

A theoretical framework which unifies the conventional Mori--Zwanzig formalism and the approximate Koopman learning of deterministic dynamical systems from noiseless observation is presented. In this framework, the Mori--Zwanzig formalism, developed in statistical mechanics to tackle the hard problem of construction of reduced-order dynamics for high-dimensional dynamical systems, can be considered as a natural generalization of the Koopman description of the dynamical system. We next show that, similar to the approximate Koopman learning methods, data-driven methods can be developed for the Mori--Zwanzig formalism with Mori's linear projection operator. We have developed two algorithms to extract the key operators, the Markov and the memory kernel, using time series of a reduced set of observables in a dynamical system. We have adopted the Lorenz `96 system as a test problem and solved for the above operators. These operators exhibit complex behaviors, which are unlikely to be captured by traditional modeling approaches in Mori--Zwanzig analysis. The nontrivial generalized fluctuation-dissipation relationship, which relates the memory kernel with the two-time correlation statistics of the orthogonal dynamics, was numerically verified as a validation of the solved operators. Here we present numerical evidence that the generalized Langevin equation, a key construct in the Mori--Zwanzig formalism, is more advantageous in predicting the evolution of the reduced set of observables than the conventional approximate Koopman operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

pnnl/FLOWER

Network FLOW analyzER - Network bi-directional deep packet header inspection. This software is designed to generate custom network flow records by monitoring bi-directional traffic from a span port, tap or other source. This function is independent of proprietary hardware or software solutions. This tool solves the problem of existing COTS solutions being either too complex or too slow.

Curtis, Darren↗
NASA NTRS1974

Effects of hypercapnia and bedrest on psychomotor performance

Two weeks of continuous exposure to simulated weightlessness (bedrest) and/or an elevated (30 torr) CO2 environment had no detrimental effect on complex tracking performance, eye-hand coordination, or problem-solving ability. These results were consistent with previously reported behavioral findings which investigated these two factors only as independent stressors.

Storm, W. F.↗
NASA NTRS1981

High power densities from high-temperature material interactions

Thermionic energy conversion (TEC) and metallic-fluid heat pipes (MFHPs), offering unique advantages in terrestrial and space energy processing by virtue of operating on working-fluid vaporization/condensation cycles that accept great thermal power densities at high temperatures, share complex materials problems. Simplified equations are presented that verify and solve such problems, suggesting the possibility of cost-effective applications in the near term for TEC and MFHP devices. Among the problems discussed are: the limitation of alkali-metal corrosion, protection against hot external gases, external and internal vaporization, interfacial reactions and diffusion, expansion coefficient matching, and creep deformation.

Morris, J. F.↗
NASA NTRS1987

Orbital resonances, unusual configurations and exotic rotation states among planetary satellites

Several examples of satellite dynamics are presented where significant progress has been made in understanding a complex problem, where a long-standing problem has finally been solved, where newly discovered configurations have motivated novel descriptions or where an entirely new phenomenon has been revealed. The origin of orbital resonances in satellites and the solution of the problem of the origin and evolution of the three body Laplace resonance among the Galilean satellites are among the topics discussed.

Peale, S. J.↗
NASA NTRS1990

Thick plate bending wave transmission using a mobility power flow approach

The mobility power flow (MPF) approach is used in this paper to describe the flexural behavior of an L-shaped plate structure consisting of thick plates with rotary inertia and shear deformation effects included in the analysis. The introduction of the thick plate effects significantly increases the complexity of the structural mobility functions used in the definitions of the power flow terms; however, because of the substructuring that is used in the MPF approach, the complexity of the problem is significantly reduced as compared to solving for the global structure. Additionally, with the MPF approach the modal behavior is described. The MPF analysis of the L-shaped plate is performed for the case of point force excitation on one plate, with the two plates being identical in both size and thickness. The results of this analysis are compared to results from the finite-element analysis (FEA) and the statistical energy analysis (SEA) and show very good agreement in the low- and high-frequency regimes, respectively.

Mccollum, M. D.↗
NASA NTRS1997

Improving Search Properties in Genetic Programming

With the advancing computer processing capabilities, practical computer applications are mostly limited by the amount of human programming required to accomplish a specific task. This necessary human participation creates many problems, such as dramatically increased cost. To alleviate the problem, computers must become more autonomous. In other words, computers must be capable to program/reprogram themselves to adapt to changing environments/tasks/demands/domains. Evolutionary computation offers potential means, but it must be advanced beyond its current practical limitations. Evolutionary algorithms model nature. They maintain a population of structures representing potential solutions to the problem at hand. These structures undergo a simulated evolution by means of mutation, crossover, and a Darwinian selective pressure. Genetic programming (GP) is the most promising example of an evolutionary algorithm. In GP, the structures that evolve are trees, which is a dramatic departure from previously used representations such as strings in genetic algorithms. The space of potential trees is defined by means of their elements: functions, which label internal nodes, and terminals, which label leaves. By attaching semantic interpretation to those elements, trees can be interpreted as computer programs (given an interpreter), evolved architectures, etc. JSC has begun exploring GP as a potential tool for its long-term project on evolving dextrous robotic capabilities. Last year we identified representation redundancies as the primary source of inefficiency in GP. Subsequently, we proposed a method to use problem constraints to reduce those redundancies, effectively reducing GP complexity. This method was implemented afterwards at the University of Missouri. This summer, we have evaluated the payoff from using problem constraints to reduce search complexity on two classes of problems: learning boolean functions and solving the forward kinematics problem. We have also developed and implemented methods to use additional problem heuristics to fine-tune the searchable space, and to use typing information to further reduce the search space. Additional improvements have been proposed, but they are yet to be explored and implemented.

Janikow, Cezary Z.↗
NASA NTRS1949

On the Theory of the Laval Nozzle

In the present paper, the motion of a gas in a plane-parallel Laval nozzle in the neighborhood of the transition from subsonic to supersonic velocities is studied. In a recently published paper, F. I. Frankl, applying the holograph method of Chaplygin, undertook a detailed investigation of the character of the flow near the line of transition from subsonic to supersonic velocities. From the results of Tricomi's investigation on the theory of differential equations of the mixed elliptic-hyperbolic type, Frankl introduced as one of the independent variables in place of the modulus of the velocity, a certain specially chosen function of this modulus. He thereby succeeded in explaining the character of the flow at the point of intersection of the transition line and the axis of symmetry (center of the nozzle) and in studying the behavior of the stream function in the neighborhood of this point by separating out the principal term having, together with its derivatives, the maximum value as compared with the corresponding corrections. This principal term is represented in Frankl's paper in the form of a linear combination of two hypergeometric functions. In order to find this linear combination, it is necessary to solve a number of boundary problems, which results in a complex analysis. In the investigation of the flow with which this paper is concerned, a second method is applied. This method is based on the transformation of the equations of motion to a form that may be called canonical for the system of differential equations of the mixed elliptic-hyperbolic type to which the system of equations of the motion of an ideal compressible fluid refers. By studying the behavior of the integrals of this system in the neighborhood of the parabolic line, the principal term of the solution is easily separated out in the form of a polynomial of the third degree. As a result, the computation of the transitional part of the nozzle is considerably simplified.

Falkovich, S. V.↗
NASA NTRSDate not supplied

Effects of Communication Delay on Human Spaceflight Missions

Missions onboard the International Space Station rely on the real-time availability of a large ground team of system experts to command the vehicle, solve safety-critical problems, and guide the crew during complex operations. Also, in Low Earth Orbit (LEO), supplies can be sent and crews evacuated quite quickly if needed. Future missions Beyond Low Earth Orbit (BLEO) will not have this 24/7, real-time safety net as communication latency increases, resupply difficulty increases, and evacuation opportunities diminish. There are few, if any, terrestrial analogs for human spaceflight missions BLEO that reflect the conditions—including extreme environments, long mission durations, and small crew sizes – that make these missions so high risk. Studies on specific conditions, such as communication delays and asynchronous interactions, have been performed in NASA Earth-based analog missions and have found that communication delays can disrupt ground-crew interactions and adversely impact team performance. However, there are gaps and limitations in studies conducted to date, notably on human spacecraft system failure response and recovery, the impacts of shorter lunar-relevant communication delays on complex operations, and the effectiveness of countermeasures. The work presented here breaks down real anomalies that occurred on ISS and Apollo missions and creates example scenarios fort Lunar Surface and Mars missions to explore the impact of communication delays of varying length on onboard operations and mission outcomes. Our analyses indicate that short communication delays (e.g., seconds to a minute) adversely impact the ability for ground to provide real-time oversight and guidance and to catch quickly emerging problems in time. Longer communication delays (e.g., up to 40 minutes on Mars missions) call for a shift of responsibility for tactical operations from ground to crew; crew must make time-critical decisions independently and respond to time-critical vehicle anomalies to prevent consequences.

human-systems integration↗
NASA NTRSDate not supplied

Effects of Communication Delay on Human Spaceflight Missions

Missions onboard the International Space Station rely on the real-time availability of a large ground team of system experts to command the vehicle, solve safety-critical problems, and guide the crew during complex operations. Also, in Low Earth Orbit (LEO), supplies can be sent and crews evacuated quite quickly if needed. Future missions Beyond Low Earth Orbit (BLEO) will not have this 24/7, real-time safety net as communication latency increases, resupply difficulty increases, and evacuation opportunities diminish. There are few, if any, terrestrial analogs for human spaceflight missions BLEO that reflect the conditions—including extreme environments, long mission durations, and small crew sizes – that make these missions so high risk. Studies on specific conditions, such as communication delays and asynchronous interactions, have been performed in NASA Earth-based analog missions and have found that communication delays can disrupt ground-crew interactions and adversely impact team performance. However, there are gaps and limitations in studies conducted to date, notably on human spacecraft system failure response and recovery, the impacts of shorter lunar-relevant communication delays on complex operations, and the effectiveness of countermeasures. The work presented here breaks down real anomalies that occurred on ISS and Apollo missions and creates example scenarios fort Lunar Surface and Mars missions to explore the impact of communication delays of varying length on onboard operations and mission outcomes. Our analyses indicate that short communication delays (e.g., seconds to a minute) adversely impact the ability for ground to provide real-time oversight and guidance and to catch quickly emerging problems in time. Longer communication delays (e.g., up to 40 minutes on Mars missions) call for a shift of responsibility for tactical operations from ground to crew; crew must make time-critical decisions independently and respond to time-critical vehicle anomalies to prevent consequences.

human-systems integration↗
DOE OSTI2024

2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

A decomposition method for optimization of large-system reliability

This paper considers a decomposition approach for optimization of the reliability of a large system with a general network structure. A 3-level methodology is developed for optimal allocation of available resources among subsystems in order to ensure maximization of system-reliability. The decentralized nature of this methodology greatly reduces the complexity of the large problem and facilitates seeking the optimal solution. Two examples show that the complexity of a large system can be greatly reduced by solving several smaller-dimensional sub-problems iteratively. Sub-problems whose dimensions are small can be efficiently solved by any existing nonlinear programming method. Another important feature of this approach is the possible simplification of the objective function during the solution. This leads in some cases to an analytic solution for the lower-level optimization problems in a 3-level decomposition solution.

Li, Duan↗
NASA NTRS1989

The evaluative imaging of mental models - Visual representations of complexity

The paper deals with some design issues involved in building a system that could visually represent the semantic structures of training materials and their underlying mental models. In particular, hypermedia-based semantic networks that instantiate classification problem solving strategies are thought to be a useful formalism for such representations; the complexity of these web structures can be best managed through visual depictions. It is also noted that a useful approach to implement in these hypermedia models would be some metrics of conceptual distance.

Dede, Christopher↗
DOE OSTI2025

Adiabatic quantum support vector machines

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic quantum approach for training support vector machines. We show that the time complexity of our quantum approach is an order of magnitude better than the classical approach. Next, we compare the test accuracy of our quantum approach against a classical approach that uses the Scikit-learn library in Python across five benchmark datasets (Iris, Wisconsin Breast Cancer (WBC), Wine, Digits, and Lambeq). We show that our quantum approach obtains accuracies on par with the classical approach. Finally, we perform a scalability study in which we compute the total training times of the quantum approach and the classical approach with an increasing number of features and an increasing number of data points in the training dataset. In conclusion, our scalability results show that the quantum approach obtains a 3.5–4.5x speedup over the classical approach on datasets with many (millions of) features.

Computational Complexity↗
NASA NTRS1973

Robot, computer problem solving system

The TENEX computer system, the ARPA network, and computer language design technology was applied to support the complex system programs. By combining the pragmatic and theoretical aspects of robot development, an approach is created which is grounded in realism, but which also has at its disposal the power that comes from looking at complex problems from an abstract analytical point of view.

Becker, J. D.↗
DOE OSTI2022

Using the Criticality Accident Alarm System modeling capabilities in SCALE [Slides]

The following is a summary of advice for CAAS modeling in SCALE. Refer to the SCALE Criticality Safety and Radiation Shielding training slides or to the SCALE manual for exact syntax. Use a mesh for the fission source that is the most adequate for the problem to solve (coarse/fine). Don’t spend unnecessary resources; simplify the model if it does not impact the final results of interest. Be careful to deactivate secondary fissions in MAVRIC or the calculation may never end. Check that k eff and $\overline{\upsilon}$ calculated results are logical. Between KENO and MAVRIC, cross section libraries, materials, geometry, and mesh grid can be the same or different. Iterative calculations are usually complex problems that need variance reduction. It will be hard to find the best solving parameters in the first attempt; expert judgement is needed. Check each step separately. Use Fulcrum to visualize fission source, mesh source, and spatial/energy distributions to find potential errors or impactful imprecisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1998

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗
DOE OSTI2022

The Ground Truth Program: Simulations as Test Beds for Social Science Research Methods.

Social systems are uniquely complex and difficult to study, but understanding them is vital to solving the world’s problems. The Ground Truth program developed a new way of testing the research methods that attempt to understand and leverage the Human Domain and its associated complexities. The program developed simulations of social systems as virtual world test beds. Not only were these simulations able to produce data on future states of the system under various circumstances and scenarios, but their causal ground truth was also explicitly known. Research teams studied these virtual worlds, facilitating deep validation of causal inference, prediction, and prescription methods. The Ground Truth program model provides a way to test and validate research methods to an extent previously impossible, and to study the intricacies and interactions of different components of research.

97 MATHEMATICS AND COMPUTING↗