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At least 235 records · Page 13

Methods for R&D Portfolio Analysis and Evaluation (Workshop Report)

The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17–18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Methods for R&D Portfolio Analysis and Evaluation (Workshop Report)

The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17-18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A comparison of the capabilities of three finite element programs

Three finite element programs are compared to assess their capabilities as an analysis tool in a structural design process. Because of the need for repetitive analyses as an integral part of a design loop, a candidate program must be capable of handling large problems, operate efficiently, and be readily adaptable for use in computer-aided design. The three programs considered in the study, ELAS,SNAP, and NASTRAN, range from a relatively small finite element program limited to static structural analysis (ELAS) to a large complex general analysis system (NASTRAN). Results are given for comparative speeds and computer resources required for each program in the analysis of sample fuselage problems representative of practical aircraft design.

Loendorf, D. D.↗

FLUT - A program for aeroelastic stability analysis

A computer program (FLUT) that can be used to evaluate the aeroelastic stability of aircraft structures in subsonic flow is described. The algorithm synthesizes data from a structural vibration analysis with an unsteady aerodynamics analysis and then performs a complex eigenvalue analysis to assess the system stability. The theoretical basis of the program is discussed with special emphasis placed on some innovative techniques which improve the efficiency of the analysis. User information needed to efficiently and successfully utilize the program is provided. In addition to identifying the required input, the flow of the program execution and some possible sources of difficulty are included. The use of the program is demonstrated with a listing of the input and output for a simple example.

Johnson, E. H.↗

A Modeling Pattern for Layered System Interfaces

Communications between systems is often initially represented at a single, high level of abstraction, a link between components. During design evolution it is usually necessary to elaborate the interface model, defining it from several different, related viewpoints and levels of abstraction. This paper presents a pattern to model such multi-layered interface architectures simply and efficiently, in a way that supports expression of technical complexity, interfaces and behavior, and analysis of complexity. Each viewpoint and layer of abstraction has its own properties and behaviors. System elements are logically connected both horizontally along the communication path, and vertically across the different layers of protocols. The performance of upper layers depends on the performance of lower layers, yet the implementation of lower layers is intentionally opaque to upper layers. Upper layers are hidden from lower layers except as sources and sinks of data. The system elements may not be linked directly at each horizontal layer but only via a communication path, and end-to-end communications may depend on intermediate components that are hidden from them, but may need to be shown in certain views and analyzed for certain purposes. This architectural model pattern uses methods described in ISO 42010, Recommended Practice for Architectural Description of Software-intensive Systems and CCSDS 311.0-M-1, Reference Architecture for Space Data Systems (RASDS). A set of useful viewpoints and views are presented, along with the associated modeling representations, stakeholders and concerns. These viewpoints, views, and concerns then inform the modeling pattern. This pattern permits viewing the system from several different perspectives and at different layers of abstraction. An external viewpoint treats the systems of interest as black boxes and focuses on the applications view, another view exposes the details of the connections and other components between the black boxes. An internal view focuses on the implementation within the systems of interest, either showing external interface bindings and specific standards that define the communication stack profile or at the level of internal behavior. Orthogonally, a horizontal view isolates a single layer and a vertical viewpoint shows all layers at a single interface point between the systems of interest. Each of these views can in turn be described from both behavioral and structural viewpoints.

Shames, Peter M.↗

Structured analysis and modeling of complex systems

The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.

Strome, David R.↗

Analysis and representation of complex structures in separated flows

We discuss our recent work on extraction and visualization of topological information in separated fluid flow data sets. As with scene analysis, an abstract representation of a large data set can greatly facilitate the understanding of complex, high-level structures. When studying flow topology, such a representation can be produced by locating and characterizing critical points in the velocity field and generating the associated stream surfaces. In 3D flows, the surface topology serves as the starting point. The 2D tangential velocity field near the surface of the body is examined for critical points. The tangential velocity field is integrated out along the principal directions of certain classes of critical points to produce curves depicting the topology of the flow near the body. The points and curves are linked to form a skeleton representing the 2D vector field topology. This skeleton provides a basis for analyzing the 3D structures associated with the flow separation. The points along the separation curves in the skeleton are used to start tangent curve integrations. Integration origins are successively refined to produce stream surfaces. The map of the global topology is completed by generating those stream surfaces associated with 3D critical points.

Helman, James↗

Modeling, analysis, and optimization of complex nuclear processes and facilities via computational methods: The HALEU process case study

Improving and adapting industrial systems to timely meet changing programmatic and market demands is an important goal to achieve, including when operating and maintaining complex nuclear processes and facilities. However, changes to these complex systems are costly, particularly when they are already in place and bounded to stringent requirements and constraints such as when handling radioactive material and contaminated equipment. These conditions often exist when treating spent nuclear fuel remotely within shielded nuclear radiation chambers, commonly referred as hot cells, to condition nuclear material and/or fabricate products for utilization in other nuclear enterprises such as in the manufacture of advanced nuclear fuel. The illustrative case considered here is the production of high assay low enriched uranium (HALEU) products supporting the deployment of advanced nuclear reactors. For the HALEU program, resources invested were and are being systematically analyzed so that these investments are maximized in a facility that is nearly 60 years old. A methodology that has effectively enabled optimized and improvements in the Spent Fuel Treatment (SFT) program, and consequently the HALEU program, involves discrete event simulation as addressed in this article. Here, the quantification of multiple productivity metrics, including material processing rates, cycle times, bottlenecks, number of material transfers as well as equipment, workstation, and material handling utilization, has resulted in a myriad of diverse discoveries and data-informed decisions regarding process layout and constituent, labor levels and schedules, selection of new process units, storage needs, and other critical process configurations. This article describes such a computational capability being applied for decision-making, illustrates its application to an actual process and program, provides illustrative results, and argues how computational methods for the modeling, analysis, and optimization of complex processes and facilities does lead to informed decisions derived from data and not only from intuition.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Contributions to Lignomics: Stochastic Generation of Oligomeric Lignin Structures for Interpretation of MALDI–FT‐ICR‐MS Results

The lack of standards to identify oligomeric molecules is a challenge for the analysis of complex organic mixtures. High-resolution mass spectrometry—specifically, Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS)—offers new opportunities for analysis of oligomers with the assignment of formulae (C x H y O z ) to detected peaks. However, matching a specific structure to a given formula remains a challenge due to the inability of FT-ICR MS to distinguish between isomers. Additional separation techniques and other analyses (e.g., NMR spectroscopy) coupled with comparison of results to those from pure compounds is one route for assignment of MS peaks. Unfortunately, this strategy may be impractical for complete analysis of complex, heterogeneous samples. In this study we use computational stochastic generation of lignin oligomers to generate a molecular library for supporting the assignment of potential candidate structures to compounds detected during FT-ICR MS analysis. Furthermore, this approach may also be feasible for other macromolecules beyond lignin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Lawrence Livermore National Laboratory Experimental Test Site 300 (S300): S300 Roadway Improvements - 817 Complex Soil Sampling and Analysis Plan (May 2023)

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Function Area (EFA)/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) for the proposed Roadway Improvements Project at the 817 Complex (project). The purpose of the SAP was to describe the procedures for collection and analysis of environmental samples and evaluation of analytical data (chemical and radiological) to determine management options of excavated soil during project construction in accordance with Lawrence Livermore National Laboratory’s (LLNL) Soils Screening and Management Plan (SSMP) (LLNL 2022), which was developed in accordance with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006) and the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance (U.S. NRC, U.S. EPA, U.S. DOE, and U.S. DOD 2000). The SAP was developed in accordance with the SSMP and based on preliminary design information provided to EFA by PMO.

54 ENVIRONMENTAL SCIENCES↗

Lawrence Livermore National Laboratory Experimental Test Site 300 (Site 300): Site 300 Roadway Improvements - 836 Complex Soil Sampling and Analysis Plan (May 2023)

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Functional Area (EFA)/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) for the proposed Roadway Improvements Project at the 836 Complex (project). The purpose of the SAP is to describe the procedures for collection and analysis of environmental samples and evaluation of analytical data (chemical and radiological) to determine management options of excavated soil during project construction. This SAP follows criteria established in Lawrence Livermore National Laboratory’s (LLNL) Soils Screening and Management Plan (SSMP) (LLNL 2022), which was formalized in accordance with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006) and the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance (U.S. NRC, U.S. EPA, U.S. DOE, and U.S. DOD 2000). The scope of this SAP is based on preliminary design information provided by PMO.

54 ENVIRONMENTAL SCIENCES↗

Quantum complexity of time evolution with chaotic Hamiltonians

We study the quantum complexity of time evolution in large-N chaotic systems, with the SYK model as our main example. This complexity is expected to increase linearly for exponential time prior to saturating at its maximum value, and is related to the length of minimal geodesics on the manifold of unitary operators that act on Hilbert space. Using the Euler-Arnold formalism, we demonstrate that there is always a geodesic between the identity and the time evolution operator e -iHt whose length grows linearly with time. This geodesic is minimal until there is an obstruction to its minimality, after which it can fail to be a minimum either locally or globally. We identify a criterion — the Eigenstate Complexity Hypothesis (ECH) — which bounds the overlap between offdiagonal energy eigenstate projectors and the k-local operators of the theory, and use it to argue that the linear geodesic will at least be a local minimum for exponential time. We show numerically that the large-N SYK model (which is chaotic) satisfies ECH and thus has no local obstructions to linear growth of complexity for exponential time, as expected from holographic duality. In contrast, we also study the case with N = 2 fermions (which is integrable) and find short-time linear complexity growth followed by oscillations. Our analysis relates complexity to familiar properties of physical theories like their spectra and the structure of energy eigenstates and has implications for the hypothesized computational complexity class separations PSPACE * BQP/poly and PSPACE * BQSUBEXP/subexp, and the “fast-forwarding” of quantum Hamiltonians.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Experimental Analysis of the Effects of Simulator Complexity on Human Performance

Human Reliability Analysis predicts accidents caused by human errors and is an important factor in Probabilistic Safety Assessment that comprehensively evaluates the safety of nuclear power plants. This study compares and analyzes the human performance of nuclear power plant operators according to the simulator complexity as part of the HRA data collection support method development project conducted by Idaho National Laboratory. This experiment was conducted by setting two types of simulators and scenarios as independent variables. The data collected by conducting the experiments in two different simulators were analyzed using an analysis of variance test and a correlation analysis, and four human performance charts were derived.

99 GENERAL AND MISCELLANEOUS↗

Site 300 Roadway Improvements - 834 Complex Soil Sampling and Analysis Plan

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Functional Area (EFA)/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) for the proposed Roadway Improvements Project at the 834 Complex (project) (Figure 1). The purpose of the SAP is to describe the procedures for collection and analysis of environmental samples and evaluation of analytical data (chemical and radiological) to determine management options of excavated soil during project construction. This SAP follows criteria established in Lawrence Livermore National Laboratory’s (LLNL) Soils Screening and Management Plan (SSMP) (LLNL 2022), which was formalized in accordance with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006) and the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance (U.S. NRC, U.S. EPA, U.S. DOE, and U.S. DOD 2000). The scope of this SAP is based on preliminary design information provided by PMO.

54 ENVIRONMENTAL SCIENCES↗

Lawrence Livermore National Laboratory Experimental Test Site, Site 300: S300 Roadway Improvements - 854 Complex Soil Sampling and Analysis Plan (June 2023)

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Functional Area (EFA)/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) for the proposed Roadway Improvements Project at the Building 854 Complex (project). The purpose of the SAP was to identify chemicals of concern, describe the procedures for collection and analysis of environmental samples, and evaluation of analytical data (chemical and radiological) to determine management options of excavated soil during project construction. This SAP follows criteria established in Lawrence Livermore National Laboratory’s (LLNL) Soils Screening and Management Plan (SSMP) (LLNL 2022), which was formalized in accordance with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006) and the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance (U.S. NRC, U.S. EPA, U.S. DOE, and U.S. DOD 2000). The scope of this SAP is based on preliminary design information provided by PMO.

54 ENVIRONMENTAL SCIENCES↗

Dynamic transformation method

Eigenvalue problem associated with modal-synthesis vibration analysis of complex structures requires simplifying assumptions for solution. Computer program, Dynamic-transformation Adapted to Modal-synthesis Using Stiffness-coupling, improves computational economy for vibration analysis of complex structures while still considering substructure modes.

Admire, J. R.↗

Hydrogen Atom Abstraction from an Os II (NH 3 ) 2 Complex Generates an Os IV (NH 2 ) 2 Complex: Experimental and Computational Analysis of the N–H Bond Dissociation Free Energies and Reactivity

We report double hydrogen atom abstraction from (TMP)Os II (NH 3 ) 2 (TMP = tetramesitylporphyrin) with phenoxyl or nitroxyl radicals leads to (TMP)Os IV (NH 2 ) 2 . This unusual bis(amide) complex is diamagnetic and displays an N-H resonance at 12.0 ppm in its 1 H NMR spectrum. 1 H- 15 N correlation experiments identified a 15 N NMR spectroscopic resonance at –267 ppm. Experimental reactivity studies and density functional theory calculations support relatively weak N-H bonds of 73.3 kcal/mol for (TMP)Os II (NH 3 ) 2 and 74.2 kcal/mol for (TMP)Os III (NH 3 )(NH 2 ). Cyclic voltammetry experiments provide an estimate of the pK a of [(TMP)Os III (NH 3 ) 2 ] + . In the presence of Barton’s base, a current enhancement is observed at the Os(III/II) couple, consistent with an ECE event. Spectroscopic experiments confirmed (TMP)Os IV (NH 2 ) 2 as the product of bulk electrolysis. Double hydrogen atom abstraction is influenced by π donation from the amides of (TMP)Os IV (NH 2 ) 2 into the d orbitals of the Os center, favoring the formation of (TMP)Os IV (NH 2 ) 2 over N-N coupling. This π donation leads to a Jahn-Teller distortion that splits the energy levels of the d xz and d yz orbitals of Os, results in a low spin electron configuration, and leads to minimal aminyl character on the N atoms, rendering (TMP)Os IV (NH 2 ) 2 unreactive towards amide-amide coupling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗