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Results for “Software behavior computation”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Behavior Computation for Smart Grid Software Analysis

Smart grid embedded software is subject to intrusion and compromise with potentially serious consequences. Current methods of cybersecurity analysis are increasingly challenged by the scope the problem. Oak Ridge National Laboratory (ORNL) is pioneering the new technology of software behavior computation to help address these risks. Software behavior computation and its instantiation in Function eXtraction (FX) systems apply mathematical foundations of denotational semantics to compute the behavior of software in all circumstances of use. Research has shown how to make the effects of recursion-theoretic limitations on this process arbitrarily small. Behavior computation operates on the functional semantics of programs, and is not subject to the limitations of syntactic recognition or testing. ORNL is applying FX technology to help evaluate cyber security properties in smart grid systems, with initial focus on vulnerabilities in embedded software that controls smart meters.

denotational semantics↗
DOE OSTI2013

Computing Legacy Software Behavior to Understand Functionality and Security Properties: An IBM/370 Demonstration

Organizations maintaining mainframe legacy software can benefit from code modernization and incorporation of security capabilities to address the current threat environment. Oak Ridge National Laboratory is developing the Hyperion system to compute the behavior of software as a means to gain understanding of software functionality and security properties. Computation of functionality is critical to revealing security attributes, which are in fact specialized functional behaviors of software. Oak Ridge is collaborating with MITRE Corporation to conduct a demonstration project to compute behavior of legacy IBM Assembly Language code for a federal agency. The ultimate goal is to understand functionality and security vulnerabilities as a basis for code modernization. This paper reports on the first phase, to define functional semantics for IBM Assembly instructions and conduct behavior computation experiments.

reverse engineering↗
DOE OSTI2015

Controlling Combinatorial Complexity in Software and Malware Behavior Computation

Virtually all software is out of intellectual control in that no one knows its full behavior. Software Behavior Computation (SBC) is a new technology for understanding everything software does. SBC applies the mathematics of denotational semantics implemented by function composition in Functional Trace Tables (FTTs) to compute the behavior of programs, expressed as disjoint cases of conditional concurrent assignments. In some circumstances, combinatorial explosions in the number of cases can occur when calculating the behavior of sequences of multiple branching structures. This paper describes computational methods that avoid combinatorial explosions. The predicates that control branching structures such as ifthenelses can be organized into three categories: 1) Independent, resulting in no behavior case explosion, 2) Coordinated, resulting in two behavior cases, or 3) Goaloriented, with potential exponential growth in the number of cases. Traditional FTT-based behavior computation can be augmented by two additional computational methods, namely, Single-Value Function Abstractions (SVFAs) and, introduced in this paper, Relational Trace Tables (RTTs). These methods can be applied to the three predicate categories to avoid combinatorial growth in behavior cases while maintaining mathematical correctness.

Hyperion system↗
DOE OSTI2012

Automated Behavior Computation for Software Analysis and Validation

Software systems can exhibit massive numbers of possi-ble execution paths, and even the most comprehensive testing can exercise only a small fraction of these. It is no surprise that systems experience errors and vulnerabilities in field use when most executions are untested. While the problem seems intractable at the execution level, it may not be so at the functional semantics level. Structured programs are expressed in a finite hierarchy of control structures, each of which corresponds to a mathematical function or relation. A correctness theo-rem defines transformation of these structures from procedural logic into non-procedural, as-built specifications of behavior. These specifications enumerate behavior for all circumstances of use and cover the behav-ior space. Automation of these computations affords a new means for validating software functionality and security properties. This paper describes theory and implementation for loop behavior computation in pa-ticular, and illustrates use of an automated behavior computation system to validate a miniature program with and without embedded malware.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Automated Vulnerability Detection for Compiled Smart Grid Software

While testing performed with proper experimental controls can provide scientifically quantifiable evidence that software does not contain unintentional vulnerabilities (bugs), it is insufficient to show that intentional vulnerabilities exist, and impractical to certify devices for the expected long lifetimes of use. For both of these needs, rigorous analysis of the software itself is essential. Automated software behavior computation applies rigorous static software analysis methods based on function extraction (FX) to compiled software to detect vulnerabilities, intentional or unintentional, and to verify critical functionality. This analysis is based on the compiled firmware, takes into account machine precision, and does not rely on heuristics or approximations early in the analysis.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Two (or more) for one: Identifying classes of household energy- and water-saving measures to understand the potential for positive spillover

A key component of behavior-based energy conservation programs is the identification of target behaviors. A common approach is to target behaviors with the greatest energy-saving potential. The concept of behavioral spillover introduces further considerations, namely that adoption of one energy-saving behavior may increase (or decrease) the likelihood of other energy-saving behaviors. This research aimed to identify and describe household energy- and water-saving measure classes within which positive spillover is likely to occur (e.g., adoption of energy-efficient appliances may correlate with adoption of water-efficient appliances), and explore demographic and psychographic predictors of each. Nearly 1,000 households in a California city were surveyed and asked to report whether they had adopted 75 different energy- and/or water-saving measures. Principal Component Analysis and Network Analysis based on correlations between adoption of these diverse measures revealed and characterized eight water-energy-saving measure classes: Water Conservation, Energy Conservation, Maintenance and Management, Efficient Appliance, Advanced Efficiency, Efficient Irrigation, Green Gardening, and Green Landscaping. Understanding these measure classes can help guide behavior-based energy program developers in selecting target behaviors and designing interventions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

GDSCalc: A Web-Based Application for Evaluating Discrete Graph Dynamical Systems

Discrete dynamical systems are used to model various realistic systems in network science, from social unrest in human populations to regulation in biological networks. A common approach is to model the agents of a system as vertices of a graph, and the pairwise interactions between agents as edges. Agents are in one of a finite set of states at each discrete time step and are assigned functions that describe how their states change based on neighborhood relations. Full characterization of state transitions of one system can give insights into fundamental behaviors of other dynamical systems. In this work, we describe a discrete graph dynamical systems (GDSs) application called GDSCalc for computing and characterizing system dynamics. It is an open access system that is used through a web interface. We provide an overview of GDS theory. This theory is the basis of the web application; i.e., an understanding of GDS provides an understanding of the software features, while abstracting away implementation details. We present a set of illustrative examples to demonstrate its use in education and research. Finally, we compare GDSCalc with other discrete dynamical system software tools. Our perspective is that no single software tool will perform all computations that may be required by all users; tools typically have particular features that are more suitable for some tasks. We situate GDSCalc within this space of software tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

BARC Element Classifier (barc)

SAND2024-02120O This program enumerates and classifies all possible functional elements in several different categories within the Ballistic Asynchronous Reversible Computing (barc) model of computation. barc software is a research tool that is being used to help document the possible digital behaviors of primitive functional elements in the ABRC a.k.a. BARC model of computation. The method of operation of this software leverages elementary concepts and methods from discrete mathematics: combinatorics (permutations), partitions and equivalence classes, symmetry transformations, and the theory of finite groups. Implementation is in Python programming language. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Frank, Michael↗
DOE OSTI2017

Thermal Tracker: The Secret Lives of Bats and Birds Revealed

Offshore wind developers and stakeholders can accelerate the sustainable, widespread deployment of offshore wind using a new open-source software program, called ThermalTracker. Researchers can now collect the data they need to better understand the potential effects of offshore wind turbines on bird and bat populations. This plug and play software can be used with any standard desktop computer, thermal camera, and statistical software to identify species and behaviors of animals in offshore locations.

17 WIND ENERGY↗
DOE OSTI2014

Angular selective window systems: Assessment of technical potential for energy savings

Static angular selective shading systems block direct sunlight and admit daylight within a specific range of incident solar angles. The objective of this study is to quantify their potential to reduce energy use and peak demand in commercial buildings using state-of-the art whole-building computer simulation software that allows accurate modeling of the behavior of optically-complex fenestration systems such as angular selective systems. Three commercial systems were evaluated: a micro-perforated screen, a tubular shading structure, and an expanded metal mesh. This evaluation was performed through computer simulation for multiple climates (Chicago, Illinois and Houston, Texas), window-to-wall ratios (0.15-0.60), building codes (ASHRAE 90.1-2004 and 2010) and lighting control configurations (with and without). The modeling of the optical complexity of the systems took advantage of the development of state-of-the-art versions of the EnergyPlus, Radiance and Window simulation tools. Results show significant reductions in perimeter zone energy use; the best system reached 28% and 47% savings, respectively without and with daylighting controls (ASHRAE 90.1-2004, south facade, Chicago,WWR=0.45). As a result, angular selectivity and thermal conductance of the angle-selective layer, as well as spectral selectivity of low-emissivity coatings, were identified as factors with significant impact on performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Biocellion Version 2.0

This work extends Biocellion 1.0 to solve advection-reaction-diffusion and incompressible Navier-Stokes partial differential equations to model water/blood flow. Biocellion is a software framework to simulate a large number of cells using high-performance parallel computers. The version 1.0 allows software users to describe biological system behaviors as a set of rules describing how individual cells behave and how cells locally interact with neighboring cells or the surrounding micro-environment. However, the version 1.0 does not support users to incorporate water/blood flow into the model, which is important to properly capture long distance communications between distant cells. This extension (version 2.0) integrates two partial differential equation solvers to the Biocellion framework to solve this limitation. Navier-Stokes equation solvers (for incompressible flow) are added to compute flow rate, and advection-reaction-diffusion equation solvers are added to update molecular concentrations considering both advection (due to flow) and local diffusion.

Kang, Seunghwa↗
DOE OSTI2024

Reduced-Order Modeling of Hydrogen Releases from Vent Stacks and with Wind

This report describes computational modeling in the HyRAM+ software for study of hydrogen behavior in two common scenarios. First, models of unignited plumes exiting a vent stack were considered. It was shown that entrainment and vent backpressure were major factors in plume physics. Second, HyRAM+ was extended to include wind effects on plumes by modifying the plume momentum balance and entrainment modeling. Use of the model showed that plume shape and length changed with wind speed and direction; in all cases, wind causes a shortening of the plume along the streamline. While the no-wind case in HyRAM+ has been validated and the newly developed wind model was fitted to very limited experimental data, more controlled experimental configurations would help validate the models and ensure accurate simulation of hydrogen plume behavior for vent stack releases or in wind.

08 HYDROGEN↗
DOE OSTI2015

Development of tritium technologies at KAERI

Korea has been operating a CANDU nuclear power plant since 1983. Tritium generated in the heavy water of the plant is removed by the Wolsong TRF (Tritium Removal Facility) and measurement campaigns of tritium near the power plant have shown the efficiency of the TRF system. The HANARO reactor uses heavy water as both reflector and moderator. In HANARO the tritiated water removal system consists of compressors, condensers, and adsorption beds. A tritium behavior analysis code (TRIBAC) for a Very High Temperature Gas-Cooled Reactor (VHTR) is under development at KAERI. The TRIBAC computer software has been equipped with models for tritium production, purification, and leakage, as well as chemisorption and tritium behavior, in the hydrogen production system. Korea takes part into the ITER program and is responsible for the supply of an SDS (Tritium Storage and Delivery System). Within this program Korea has launched an experimental program to study the physico-chemical properties of metal and their hydrides in which hydrogen isotope gases can be stored and removed safely.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Quantum Accelerators for High-performance Computing Systems

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, the prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.

Humble, Travis↗
DOE OSTI2020

Cutting the Deployment Costs of Physics-Based MPC in Buildings by Simulation-Based Imitation Learning

It has been shown that model predictive control (MPC) is a promising solution for energy-efficient building operations. However, the deployment of MPC in a large portion of the building stock has not been possible partially because of high installation costs. Every building is unique and requires a tailored MPC solution. The best performing solutions are often based on physics-based modeling, which is, however, computationally expensive and requires dedicated software. A promising direction that tackles this problem is to train a neural network-based optimal control policy to imitate the behavior of physics-based MPC from the simulation data generated offline. The neural networks give control actions that closely approximate those produced by physics-based MPC, but with a fraction of the computational and memory requirements and without the need for licensed software. The main advantage of the proposed approach stems from simple evaluation at execution time, leading to low computational footprints and easy deployment on embedded HW platforms. In the case study, we present the energy savings potential of physics-based MPC applied to an office building in Belgium. We demonstrate how neural network approximators can be used to cut the implementation and maintenance costs of MPC deployment without compromising performance. We also critically assess the presented approach by pointing out the remaining challenges and open research questions.

Drgona, Jan↗
DOE OSTI2026

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗
DOE OSTI2020

Multiphysics for nuclear energy applications using a cohesive computational framework

With the recent development of advanced numerical algorithms, software design, and low-cost high-performance computer hardware, reliance on coupled multiphysics to predict the behavior of complex physical systems is beginning to become standard practice. This is especially true in nuclear energy applications where strong nonlinear interdependencies exist between reactor physics, radiation transport, multi-scale nuclear fuels performance, thermal fluids, etc. Resolving these nonlinear dependencies requires choices in multiphysics software approaches. Two main multiphysics modeling and simulation approaches have emerged. The first is based upon "code coupling" where disparate physics codes of different software design, code languages, and spatial and temporal integration schemes are coupled together with relatively complex data passing interfaces. The second multiphysics software approach is to employ a "cohesive" framework where all physics applications are developed with a common software design, i.e., data structures, syntax, input format, integrated spatial and temporal discretization schemes, etc. In this paper we present the Multiphysics Object-Oriented Simulation Environment (MOOSE) development and runtime framework and describe the framework's cohesive modeling and simulation multiphysics approach. Then, a "cohesive-like" extension of the MOOSE framework is presented where MOOSE-based physics software applications are efficiently coupled to non-MOOSE (external) physics codes to form multiphysics applications using MOOSE's unique interface capabilities. Finally, several examples of MOOSE's cohesive and cohesive-like multiphysics applications will be demonstrated. These multiphysics demonstrations will incorporate both MOOSE-based applications and external codes, including Nek5000, RELAP-7, TRACE, BISON, and Pronghorn.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗