Results for “Software Construction” — Page 14

DOE OSTI2018

Parallel Fenics Implementation of Block Solvers (pFibs)

This software is a Python package designed to act as an interface between FEniCS and PETSc to facilitate the construction and application of parallel block solvers/preconditioners. The original intent of this software was to help enable Battery and Wind Farm simulations for use on high performance computing systems. The code is written in Python and uses the petsc4py module to access the more advance features of the PETSc Krylov Solver. In essence, pFibs is an interface to make accessing these features more streamlined. Additionally, pFibs also provides a template for building custom Python based preconditioning algorithms.

Allen, Jeffery↗

NASA NTRS1994

A toolbox and record for scientific models

Computational science presents a host of challenges for the field of knowledge-based software design. Scientific computation models are difficult to construct. Models constructed by one scientist are easily misapplied by other scientists to problems for which they are not well-suited. Finally, models constructed by one scientist are difficult for others to modify or extend to handle new types of problems. Construction of scientific models actually involves much more than the mechanics of building a single computational model. In the course of developing a model, a scientist will often test a candidate model against experimental data or against a priori expectations. Test results often lead to revisions of the model and a consequent need for additional testing. During a single model development session, a scientist typically examines a whole series of alternative models, each using different simplifying assumptions or modeling techniques. A useful scientific software design tool must support these aspects of the model development process as well. In particular, it should propose and carry out tests of candidate models. It should analyze test results and identify models and parts of models that must be changed. It should determine what types of changes can potentially cure a given negative test result. It should organize candidate models, test data, and test results into a coherent record of the development process. Finally, it should exploit the development record for two purposes: (1) automatically determining the applicability of a scientific model to a given problem; (2) supporting revision of a scientific model to handle a new type of problem. Existing knowledge-based software design tools must be extended in order to provide these facilities.

Ellman, Thomas↗

NASA NTRS2009

Deriving Safety Cases from Automatically Constructed Proofs

Formal proofs provide detailed justification for the validity of claims and are widely used in formal software development methods. However, they are often complex and difficult to understand, because the formalism in which they are constructed and encoded is usually machine-oriented, and they may also be based on assumptions that are not justified. This causes concerns about the trustworthiness of using formal proofs as arguments in safety-critical applications. Here, we present an approach to develop safety cases that correspond to formal proofs found by automated theorem provers and reveal the underlying argumentation structure and top-level assumptions. We concentrate on natural deduction style proofs, which are closer to human reasoning than resolution proofs, and show how to construct the safety cases by covering the natural deduction proof tree with corresponding safety case fragments. We also abstract away logical book-keeping steps, which reduces the size of the constructed safety cases. We show how the approach can be applied to the proofs found by the Muscadet prover.

Basir, Nurlida↗

NASA NTRS1986

An empirical study of flight control software reliability

The results of a laboratory experiment in flight control software reliability are reported. The experiment tests a small sample of implementations of a pitch axis control law for a PA28 aircraft with over 14 million pitch commands with varying levels of additive input and feedback noise. The testing which uses the method of n-version programming for error detection surfaced four software faults in one implementation of the control law. The small number of detected faults precluded the conduct of the error burst analyses. The pitch axis problem provides data for use in constructing a model in the prediction of the reliability of software in systems with feedback. The study is undertaken to find means to perform reliability evaluations of flight control software.

Dunham, J. R.↗

DOE OSTI2021

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

42 ENGINEERING↗

DOE OSTI2021

Development of the IES Plug-and-Play Framework

This report discusses the status of the flexible plug-and-play framework development currently ongoing that aims to integrate Modelica/Dymola with the Risk Analysis and Virtual ENvironment (RAVEN) software in terms of both Functional Mock-Up Interface (FMI)/Functional Mock-Up Unit (FMU) construction and repository structures that aim to ease the sharing and simulation of complex dynamic models. This report aims to provide an overview of all the performed activities resolving around the deployment of methods, software infrastructures, guidelines and workflow for the construction and usage of models, encapsulated using the FMI/FMU protocols and standards. In particular, the report is organized in three main macro-subjects, which are connected to each other: - FMI/FMU adaptors for modelica models - HYBRID repository new structure and open-source deployment - RAVEN FMI/FMU exporting capabilities and Artificial Intelligence (AI)-based analysis acceleration. The first part of the report discusses the FMI/FMU adaptors that have been created within the HYBRID repository to allow users to quickly export models, such as FMUs. Several examples are shown that highlight the step-by-step process of converting an existing Modelica model into an FMU for use within the Dymola platform. Simulation results demonstrate that, while minor differences may occur, the overall control, trends, and solution integrity are maintained between standard Modelica simulation and FMU simulation results. However, it is worth noting that, for small systems, the FMU results have a slower simulation time than the Modelica only simulation. Using this process, a company can provide models that contain proprietary information to entities without disclosing any of the information about the model that could be considered business sensitive. Such an ability would allow institutions to bypass the necessity of “whitewashing” data. In the second part of the report, the new structure of the HYBRID repository is discussed with a major focus on the series of updates that has been completed. These updates include the addition of Modelica system-level regression tests and software quality assurance documentation that ensure that modifications to the Modelica models do not alter system-level model results. The third and final part of the report aims to report the work that has been performed for the deployment of methods and workflows for the construction of RAVEN AI-based models compliant with the FMI/FMU standard. Such development represents the key for the deployment of the concept of “Flexible ecosystem” since it allows for the replacement of high-fidelity modelica models (or any other FMI/FMU compliant model) with RAVEN generated AI surrogate models. Overall, extensive work has been completed on developing FMUs and FMIs from existing models, understanding the requirements and limitations of FMUs, and open-sourcing the HYBRID repository with an integrated regression system.

14 SOLAR ENERGY↗

NASA NTRS2020

Integrating the Science Opportunity Analyzer with a Reusable Opportunity Search Framework

In our interactions with the Science Opportunity Analyzer (SOA) software, we recognized how its ability to search for geometric events in space is a need for robotic space missions in general. To satisfy this need, we propose the Tychonis framework, which is built upon the principles of: (1) separations of concerns, (2) extensibility, (3) reusability, and (4) independent verification and validation. Tychonis’ separation of concerns results in the availability of different constructs to model geometric events and search for them. These constructs can be extended by users as needed and reused across missions without changes. Given the low coupling between concerns, and the fact Tychonis can be augmented in isolation, its constructs can be validated independently from other pieces of software. This paper elaborates on these topics and presents an integration case study between Tychonis and SOA that relies on the concept of dynamic integration. Dynamic integration entails that augmentations of the framework are reflected automatically in the host application without any changes to the host application’s code. The SOA-Tychonis integration case study can be extrapolated to other tools that need to search for geometric events as the pattern repeats across implementations: (i) the manipulation of a user interface to model opportunities, (ii) the execution of algorithms to search for opportunities, and (iii) the presentation of search results to users. Overall, Tychonis’ is a story about how the application of proven software principles and good design choices can reduce risk and cost to space missions

Soria, Manel↗

NASA NTRS1992

Providing an empirical basis for optimizing the verification and testing phases of software development

Applying equal testing and verification effort to all parts of a software system is not very efficient, especially when resources are limited and scheduling is tight. Therefore, one needs to be able to differentiate low/high fault density components so that the testing/verification effort can be concentrated where needed. Such a strategy is expected to detect more faults and thus improve the resulting reliability of the overall system. This paper presents an alternative approach for constructing such models that is intended to fulfill specific software engineering needs (i.e. dealing with partial/incomplete information and creating models that are easy to interpret). Our approach to classification is as follows: (1) to measure the software system to be considered; and (2) to build multivariate stochastic models for prediction. We present experimental results obtained by classifying FORTRAN components developed at the NASA/GSFC into two fault density classes: low and high. Also we evaluate the accuracy of the model and the insights it provides into the software process.

Briand, Lionel C.↗

NASA NTRS1991

A software development and evolution model based on decision-making

Design is a complex activity whose purpose is to construct an artifact which satisfies a set of constraints and requirements. However the design process is not well understood. The software design and evolution process is the focus of interest, and a three dimensional software development space organized around a decision-making paradigm is presented. An initial instantiation of this model called 3DPM(sub p) which was partly implemented, is presented. Discussion of the use of this model in software reuse and process management is given.

Wild, J. Christian↗

DOE OSTI2019

A Thermodynamic Model Toward the Comprehension of Ferrous Burden Softening and Melting Using FactSage Macro-Processing

The softening and melting properties of iron-bearing materials play a decisive role in the formation of the cohesive zone, which greatly affects blast furnace gas flow distribution and heat-transfer efficiency. To improve the understanding regarding the evolution of condensed phases during reduction, softening, and melting, a thermodynamic model has been developed using FactSage™ thermodynamic software and macro-processing. The model was constructed using a series of equilibrium stages and splitters to determine flow directions of streams and to consider kinetic inhibitions. For all iron-bearing materials studied, the methodology proposed for modeling was capable of obtaining reduction degrees in very good agreement to its experimental data. The evolution of solid phases was qualitatively comparable to the available literature, with Fayalite, Kirschsteinite, Melilite, and FeO as the main solid phases in equilibrium before slag formation. The comparison between the profiles of the calculated slag mass fraction and the experimental pressure drop showed a close relation between these properties. Moreover, the level of heterogeneity of each raw material may play a significant role in the interpretation of its results.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Extending particle tracking capability with Delaunay triangulation

Here, particle tracking, the analysis of individual moving elements in time series of microscopic images, enables burgeoning new applications, but there is need to better resolve conformation and dynamics. Here we describe the advantages of Delaunay triangulation to extend the capabilities of particle tracking in three areas: (1) discriminating irregularly shaped objects, which allows one to track items other than point features; (2) combining time and space to better connect missing frames in trajectories; and (3) identifying shape backbone. To demonstrate the method, specific examples are given, involving analyzing the time-dependent molecular conformations of actin filaments and λ-DNA. The main limitation of this method, shared by all other clustering techniques, is the difficulty to separate objects when they are very close. This can be mitigated by inspecting locally to remove edges that are longer than their neighbors and also edges that link two objects, using methods described here, so that the combination of Delaunay triangulation with edge removal can be robustly applied to processing large data sets. As common software packages, both commercial and open source, can construct Delaunay triangulation on command, the methods described in this paper are both computationally efficient and easy to implement.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Microservices Architecture Toolkit for Interconnected Science Ecosystems

Microservices architecture is a promising approach for developing reusable scientific workflow capabilities for inte- grating diverse resources, such as experimental and observational instruments and advanced computational and data management systems, across many distributed organizations and facilities. In this paper, we describe how the INTERSECT Open Architec- ture leverages federated systems of microservices to construct interconnected science ecosystems, review how the INTERSECT software development kit eases microservice capability develop- ment, and demonstrate the use of such capabilities for deploying an example multi-facility INTERSECT ecosystem.

Brim, Michael↗

DOE OSTI2016

A frequentist approach to computer model calibration

The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes a new and identifiable parameterization of the calibration problem. It also develops a two-step procedure for estimating all the relevant quantities under the new parameterization. This estimation procedure is shown to enjoy excellent rates of convergence and can be straightforwardly implemented with existing software. For uncertainty quantification, bootstrapping is adopted to construct confidence regions for the quantities of interest. As a result, the practical performance of the methodology is illustrated through simulation examples and an application to a computational fluid dynamics model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

EI_MS_ML

The unambiguous identification of compounds from their electron ionization mass (EI-MS) spectra remains a significant unsolved problem in the field of metabolomics and analytical chemistry as a whole. Typically EI-MS spectra are compared using various mathematical operations that convert the spectral similarity or differences into a distance-like metric that roughly approximates the similarity of any two spectra. A commonly used metric for this is the cosine similarity metric which has values close to one for very similar spectra and a value of zero for very dissimilar spectra; however, no metric is perfect. Due to the prevalence of structurally-similar compounds such as isomers and the prevalence of certain fragmentation patterns across structurally-dissimilar compounds, the unambiguous assignment of EI-MS spectra compounds remains difficult. Frequently, querying an observed EI-MS spectrum against a large database such as the NIST17 library yields multiple possible assignments requiring the end user to distinguish between multiple high scoring hits, or multiple low scoring hits while keeping in mind that the correct hit may not be in the database at all. Although techniques such as orthogonal information from techniques such as chromatography can greatly aid in unambiguous assignment, this also requires more complicated experimental designs and access to more complicated analytical instrumentation. Substructures can be trivially detected and represented as strings using a previously published technique called node coloring from a known chemical structure. However, for experimentally-derived EI-MS spectra this information must be derived from the spectra itself (i.e., because we do not know what compound it represents). To achieve this, the software uses techniques from the field of machine learning and a large training dataset of EI-MS spectra corresponding to known structures annotated with substructure strings, to build models that can predict the presence of a given chemical substructure from an EI-MS spectrum directly.If these predictions are of high-quality (i.e., are unlikely to be false positives), the presence of one or more predicted substructures can be used to constrain the number of possible hits for a query spectrum. Mathematically, this restriction could be expressed in many forms, but the most straight-forward implementation is to weight the cosine similarity of a query spectrum and a plausible database match with a Tanimoto-like coefficient based on the ratio of the number of substructures predicted to the number of substructures present in the potential database hit. Determining which combination of models best reduces assignment ambiguity will be achieved using a combination of manual curation and optimization techniques such as genetic algorithms. This software will perform all the steps necessary to construct said models from a training dataset and evaluate them using a holdout dataset. Various statistical analyses can be performed to determine if this approach does decrease assignment ambiguity. For example, if this approach works, on average, the rank-order of the correct assignment for the holdout set of EI-MS spectra should decrease and the weighted cosine similarities for most of the possible matches in the database should be better than the unweighted cosine similarities. Furthermore, this same pipeline can be used on real experimental data to generate less ambiguous assignments.

Mitchell, Joshua↗

DOE OSTI2018

High Precision RF Control for SRF Cavities in LCLS-II

The unique properties of SRF cavities enable a new generation of X-ray light sources in XFEL and LCLS-II. The LCLS-II design calls for 280 L-band cavities to be operated in CW mode with a Q_{L} of 4x10⁷, using Single-Source Single-Cavity control. The target RF field stability is 0.01% and 0.01 degree for the band above 1 Hz. Hardware and software implementing a digital LLRF system has been constructed by a four-lab collaboration to minimize known contributors to cavity RF field fluctuation. Efforts include careful attachment to the phase reference line, and minimizing the effects of RF crosstalk by placing forward and reverse signals in chassis separate from the cavity measurement. A low-noise receiver/digitizer section will allow feedback to operate with high proportional gain without excessive noise being sent to the drive amplifier. Test results will show behavior on prototype cryomodules at FNAL and JLab, ahead of the 2018 final accelerator installation.

43 PARTICLE ACCELERATORS↗

NASA NTRS1976

LUMIS: Land Use Management and Information Systems; coordinate oriented program documentation

An integrated geographic information system to assist program managers and planning groups in metropolitan regions is presented. The series of computer software programs and procedures involved in data base construction uses the census DIME file and point-in-polygon architectures. The system is described in two parts: (1) instructions to operators with regard to digitizing and editing procedures, and (2) application of data base construction algorithms to achieve map registration, assure the topological integrity of polygon files, and tabulate land use acreages within administrative districts.

Source record↗

NASA NTRS1982

Design and evaluation of a fault-tolerant multiprocessor using hardware recovery blocks

A fault-tolerant multiprocessor with a rollback recovery mechanism is discussed. The rollback mechanism is based on the hardware recovery block which is a hardware equivalent to the software recovery block. The hardware recovery block is constructed by consecutive state-save operations and several state-save units in every processor and memory module. When a fault is detected, the multiprocessor reconfigures itself to replace the faulty component and then the process originally assigned to the faulty component retreats to one of the previously saved states in order to resume fault-free execution. A mathematical model is proposed to calculate both the coverage of multi-step rollback recovery and the risk of restart. A performance evaluation in terms of task execution time is also presented.

Lee, Y. H.↗

NASA NTRS1989

Evaluation of power control concepts using the PMAD systems test bed

The Lewis Research Center's Power Management and Distribution (PMAD) System testbed and its use in the evaluation of control concepts applicable to the NASA Space Station Freedom electric power system (EPS) are described. The facility was constructed to allow testing of control hardware and software in an environment functionally similar to the space station electric power system. Control hardware and software have been developed to allow operation of the testbed power system in a manner similar to a supervisory control and data acquisition (SCADA) system employed by utility power systems for control. The system hardware and software are described.

Beach, R. F.↗