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At least 1,027 records · Page 57

Processing of Ice Cloud In Situ Data Collected by Bulk Water, Scattering, and Imaging Probes: Fundamentals, Uncertainties, and Efforts toward Consistency

Abstract In situ observations of cloud properties made by airborne probes play a critical role in ice cloud research through their role in process studies, parameterization development, and evaluation of simulations and remote sensing retrievals. To determine how cloud properties vary with environmental conditions, in situ data collected during different field projects processed by different groups must be used. However, because of the diverse algorithms and codes that are used to process measurements, it can be challenging to compare the results. Therefore it is vital to understand both the limitations of specific probes and uncertainties introduced by processing algorithms. Since there is currently no universally accepted framework regarding how in situ measurements should be processed, there is a need for a general reference that describes the most commonly applied algorithms along with their strengths and weaknesses. Methods used to process data from bulk water probes, single-particle light-scattering spectrometers and cloud-imaging probes are reviewed herein, with emphasis on measurements of the ice phase. Particular attention is paid to how uncertainties, caveats, and assumptions in processing algorithms affect derived products since there is currently no consensus on the optimal way of analyzing data. Recommendations for improving the analysis and interpretation of in situ data include the following: establishment of a common reference library of individual processing algorithms, better documentation of assumptions used in these algorithms, development and maintenance of sustainable community software for processing in situ observations, and more studies that compare different algorithms with the same benchmark datasets.

54 ENVIRONMENTAL SCIENCES↗

Underground Test Area Activity Quality Assurance Plan Nevada National Security Site, Nevada. Revision 2

This Quality Assurance Plan (QAP) provides the overall quality assurance (QA) requirements and general quality practices to be applied to the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) Underground Test Area (UGTA) activities. The requirements in this QAP are consistent with DOE Order 414.1D, Change 1, Quality Assurance (DOE, 2013a); U.S. Environmental Protection Agency (EPA) Guidance for Quality Assurance Project Plans for Modeling (EPA, 2002); and EPA Guidance on the Development, Evaluation, and Application of Environmental Models (EPA, 2009). If a participant’s requirement document differs from this QAP, the stricter requirement will take precedence. NNSA/NFO, or designee, must review this QAP every two years. Changes that do not affect the overall scope or requirements will not require an immediate QAP revision but will be incorporated into the next revision cycle after identification. Section 1.0 describes UGTA objectives, participant responsibilities, and administrative and management quality requirements (i.e., training, records, procurement). Section 1.0 also details data management and computer software requirements. Section 2.0 establishes the requirements to ensure newly collected data are valid, existing data uses are appropriate, and environmental-modeling methods are reliable. Section 3.0 provides feedback loops through assessments and reports to management. Section 4.0 provides the framework for corrective actions. Section 5.0 provides references for this document.

54 ENVIRONMENTAL SCIENCES↗

Livermore Compiler Analysis Loop Suite

LCALS is designed to evaluate compiler optimizations and performance of a variety of loop kernels and loop traversal software constructs. Some of the loop kernels are pulled directly from "Livermore Loops Coded in C", developed at LLNL (see item 11 below for details of earlier code versions). The older suites were used to evaluate floating-point performances of hardware platforms prior to porting larger application codes. The LCALS suite is geared toward assissing C++ compiler optimizations and platform performance related to SIMD vectorization, OpenMP threading, and advanced C++ language features. LCALS contains 20 of 24 loop kernels from the older Livermore Loop suites, plus various others representative of loops found in current production appkication codes at LLNL. The latter loops emphasize more diverse loop constructs and data access patterns than the others, such as multi-dimensional difference stencils. The loops are included in a configurable framework, which allows control of compilation, loop sampling for execution timing, which loops are run and their lengths. It generates timing statistics for analysis and comparing variants of individual loops. Also, it is easy to add loops to the suite as desired.

Hornung, R. D.↗

Testing contamination source identification methods for water distribution networks

In the event of contamination in a water distribution network (WDN), source identification (SI) methods that analyze sensor data can be used to identify the source location(s). Knowledge of the source location and characteristics are important to inform contamination control and cleanup operations. Various SI strategies that have been developed by researchers differ in their underlying assumptions and solution techniques. The following manuscript presents a systematic procedure for testing and evaluating SI methods. The performance of these SI methods is affected by various factors including the size of WDN model, measurement error, modeling error, time and number of contaminant injections, and time and number of measurements. This paper includes test cases that vary these factors and evaluates three SI methods on the basis of accuracy and specificity. The tests are used to review and compare these different SI methods, highlighting their strengths in handling various identification scenarios. These SI methods and a testing framework that includes the test cases and analysis tools presented in this paper have been integrated into EPA’s Water Security Toolkit (WST), a suite of software tools to help researchers and others in the water industry evaluate and plan various response strategies in case of a contamination incident. Lastly, a set of recommendations are made for users to consider when working with different categories of SI methods.

54 ENVIRONMENTAL SCIENCES↗

Safeguards and security modeling for electrochemical plants

Safeguards and security design for reprocessing plants can lead to excessive costs if not incorporated early in the design process. The design for electrochemical plants is somewhat uncertain since these plants have not been built at a commercial scale in the past. The Separation and Safeguards Performance Model (SSPM), developed at Sandia National Laboratories, has been used for safeguards design and evaluation for multiple reprocessing plant types. The SSPM includes the following capabilities: -) spent fuel source term library, -) mass tracking of elements 1-99 and bulk solid/liquids, -) tracking of heat load and activity, -) customisable measurement points, -) automated calculation of ID and error propagation, -) alarm conditions and statistical tests, and -) user-defined diversion scenarios. Materials accountancy and process monitoring data can provide more timely detection of material loss specifically to protect against the insider threat. While the SSPM is capable of determining detection probabilities and examining detection times for material loss scenarios, it does not model the operations or spatial effects for a plant design. The STAGE software was chosen to model the physical protection system. STAGE provides a framework to create end-to-end scalable force-on-force combat simulations. It allows for a complete 3D model of a facility to be designed along with the design of physical protection elements. This software, then, can be used to model operations and response for various material loss scenarios. The future integration of the SSPM model data with the STAGE software will provide a more complete analysis of diversion scenarios to assist plant designers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective

Advances in computational metabolic optimization are required to realize the full potential of new in vivo metabolic engineering technologies by bridging the gap between computational design and strain development. We present Redirector, a new Flux Balance Analysis-based framework for identifying engineering targets to optimize metabolite production in complex pathways. Previous optimization frameworks have modeled metabolic alterations as directly controlling fluxes by setting particular flux bounds. Redirector develops a more biologically relevant approach, modeling metabolic alterations as changes in the balance of metabolic objectives in the system. This framework iteratively selects enzyme targets, adds the associated reaction fluxes to the metabolic objective, thereby incentivizing flux towards the production of a metabolite of interest. These adjustments to the objective act in competition with cellular growth and represent up-regulation and down-regulation of enzyme mediated reactions. Using the iAF1260 E. coli metabolic network model for optimization of fatty acid production as a test case, Redirector generates designs with as many as 39 simultaneous and 111 unique engineering targets. These designs discover proven in vivo targets, novel supporting pathways and relevant interdependencies, many of which cannot be predicted by other methods. Redirector is available as open and free software, scalable to computational resources, and powerful enough to find all known enzyme targets for fatty acid production.

59 BASIC BIOLOGICAL SCIENCES↗

Design of the Next Generation Target at the Lujan Neutron Scattering Center, LANSCE

Los Alamos National Laboratory (LANL) supports scientific research in many diverse fields such as biology, chemistry, and nuclear science. The Laboratory was established in 1943 during the Second World War to develop nuclear weapons. Today, LANL is one of the largest laboratories dedicated to nuclear defense and operates an 800 MeV proton linear accelerator for basic and applied research including: production of high- and low-energy neutrons beams, isotope production for medical applications and proton radiography. This accelerator is located at the Los Alamos Neutron Science Center (LANSCE). The work performed involved the redesign of the target for the low-energy neutron source at the Lujan Neutron Scattering Center, which is one of the facilities built around the accelerator. The redesign of the target involves modeling various arrangements of the moderator-reflector-shield for the next generation neutron production target. This is done using Monte Carlo N-Particle eXtended (MCNPX), and ROOT analysis framework, a C++ based-software, to analyze the results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Use Case-Informed Framework for Utility Cloud Migration

This white paper presents a comprehensive methodology for assessing utilities’ cloud postures and frameworks. It aims to produce a roadmap and strategy for a cloud-enabled grid future, providing guidance for integrators, asset owners, and operators. Instead of offering a yes or no answer for cloud implementation, this framework offers strategic guidance on responsibly preparing for and deploying cloud solutions. This paper delves into cloud-service models pertinent to the electric sector, dissecting the shared responsibility model and elucidating what on-premise infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) entail. A pivotal consideration within the context of the shared responsibility model is the allocation of responsibility for foundational security aspects—a decision that will be informed by a comprehensive risk assessment. The ensuing discussion will present a checklist of certifications necessary for a secure cloud transition, equipping utilities with the knowledge to navigate this digital transformation with confidence and with a strategic roadmap. Furthermore, the paper outlines gaps in understanding the U.S. government’s role in shaping technology development and responsible use. Its purpose is to aid decision-making by offering support for risk-informed solutions that benefit those managing assets and operating in the cloud environment. The primary objective is to enhance the resilience and future readiness of a decarbonized electric grid, with cloud solutions as one viable option. The paper synthesizes information on current and future grid architectures and applications, considering both conservative and progressive energy transitions, along with scalable and distributed computing considerations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

FAUST - Benchmark and Validation Framework [Slides]

This presentation discusses Python packages for nuclear data applications and for benchmarking. It also discusses the goals and objectives for FAUST which include providing input and output processing for different calculation codes, allowing for exchanging results between different applications and codes, running benchmarks and processing the results, automating and simplify plot and report generation, and providing a basis for developing applications useful for nuclear data evaluators. The presentation also discusses how the packages can be used both inside and outside LANL.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Exascale Virtualized and Programmable Distributed Cyber Resource Control: Final Scientific Technical Report

Extreme-science drives the need for distributed exascale processing and communications that are carefully, yet flexibly, managed. Exponential growth of data for scientific simulations, experimental data, collaborative data analyses, remote visualization and GRID computing requirements of scientists in fields as diverse as high energy physics, climate change, genomics, fusion, synchrotron radiation, material science, medicine, and other scientific disciplines cannot be accommodated by simply applying existing transport protocols to faster pipes. Further, scientific challenges today demand diverse research teams, heightening the need for and increasing the complexity of collaboration. To address these issues within the network layer and physical layer, we have performed a number of research activities surrounding effective allocation and management of elastic optical network (EON) resources, particularly focusing on FlexGrid transponders. FlexGrid transponders support the opportunity to build Layer-1 connections at a wide range of bandwidths and to reconfigure them rapidly. The new flexibility supports complex new ways of using the physical layer that must be carefully managed and hidden from the scientist end-users. FlexGrid networks utilize flexible (or elastic) spectral bandwidths for each data link without using fixed wavelength grids. The flexibility in spectrum allocation brings many appealing features to network operations. Current networks are designed for the worst case impairments in transmission performance and the assigned spectrum is over-provisioned. In contrast, the FlexGrid networks can operate with the highest spectral efficiency and minimum bandwidth for the given traffic demand while meeting the minimum quality of transmission (QoT) requirement. Two primary focuses of our research are: (1) resource and spectrum allocation (RSA) for IP traffic over EONs, and (2) RSA for cross-domain optical networks. Previous work concentrates primarily on large file transfers within a single domain. Adding support for IP traffic changes the nature of the RSA problem: instead of choosing to accept or deny each request for network support, IP traffic is inherently elastic and thus lends itself to a bandwidth maximization formulation. We developed a number of algorithms that could be easily deployed within existing and new FlexGrid networks, leading to networks that better support scientific collaboration. Cross-domain RSA research is essential to support large-scale FlexGrid networks, since configuration information is generally not shared or coordinated across domains. The results presented here are in their early stages. They are technically feasible and practical, but still require coordination among organizations and equipment owners and a higher-layer framework for managing network requests.

42 ENGINEERING↗

Catalyst Revised: Rethinking the ParaView in Situ Analysis and Visualization API

As in situ analysis goes mainstream, ease of development, deployment, and maintenance becomes essential, perhaps more so than raw capabilities. In this paper, we present the design and implementation of Catalyst, an API for in situ analysis using ParaView, which we refactored with these objectives in mind. Furthermore, our implementation combines design ideas from in situ frameworks and HPC tools like Ascent and MPICH.

97 MATHEMATICS AND COMPUTING↗

Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO 2 -spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

36 MATERIALS SCIENCE↗

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Abstract Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

59 BASIC BIOLOGICAL SCIENCES↗

A study of fluid-structure interaction on overlapping grids with a focus on flexible beams

Fluid-structure interaction problems appear in many areas of science and engineering. Adequately understanding these problems is crucial to the study of such disciplines as aeroelastic flutter, wind turbine performance, implosions and explosions, and hemodynamics, to name a few. One technique to explore these problems is the use of numerical simulations. Although methods for the accurate and efficient numerical simulation of many problems involving only flexible structures or those involving only fluids have existed for a long time, the simulation of coupled problems, in which a flexible structure (or structures) interact with fluids remains challenging. The source of the difficulty with these problems is the construction of schemes for the coupling between the fluid and the solid that are both accurate and stable. There are two general approaches to designing a coupling procedure. In the first, the so-called monolithic approach, a single solver is implemented that handles both the fluid equations and the solid equations in a single framework. In this scheme, the solver handles the fluid and solid equations simultaneously, resulting in a strong coupling between the two. The second approach, named the partitioned approach, handles the fluid and structure domains separately. Whereas in the monolithic scheme there is a single solver for both the fluid and the structure, in the partitioned scheme there are separate solvers for the fluid and the structure. This separation heavily restricts the communication and coordination that can occur between the two solvers. Typically the only communication done in these schemes is through the application of boundary conditions (where the fluid applies a boundary condition on the fluid, and the solid one (or more) on the fluid). This makes the implementation of partitioned schemes easy, especially because they can take advantage of existing algorithms and software developed for the simulation of fluid flow or computational mechanics. However, they have a weakness – accuracy and stability are much harder to achieve. Stability is a particular problem for these schemes, as they are prone to the so-called added-mass effect.

97 MATHEMATICS AND COMPUTING↗

The Athena++ Adaptive Mesh Refinement Framework: Design and Magnetohydrodynamic Solvers

The design and implementation of a new framework for adaptive mesh refinement calculations are described. It is intended primarily for applications in astrophysical fluid dynamics, but its flexible and modular design enables its use for a wide variety of physics. The framework works with both uniform and nonuniform grids in Cartesian and curvilinear coordinate systems. It adopts a dynamic execution model based on a simple design called a "task list" that improves parallel performance by overlapping communication and computation, simplifies the inclusion of a diverse range of physics, and even enables multiphysics models involving different physics in different regions of the calculation. We describe physics modules implemented in this framework for both nonrelativistic and relativistic magnetohydrodynamics (MHD). These modules adopt mature and robust algorithms originally developed for the Athena MHD code and incorporate new extensions: support for curvilinear coordinates, higher-order time integrators, more realistic physics such as a general equation of state, and diffusion terms that can be integrated with super-time-stepping algorithms. The modules show excellent performance and scaling, with well over 80% parallel efficiency on over half a million threads. The source code has been made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

Classifying topology in photonic crystal slabs with radiative environments

Abstract In the recent years, photonic Chern materials have attracted substantial interest as they feature topological edge states that are robust against disorder, promising to realize defect-agnostic integrated photonic crystal slab devices. However, the out-of-plane radiative losses in those photonic Chern slabs has been previously neglected, yielding limited accuracy for predictions of these systems’ topological protection. Here, we develop a general framework for measuring the topological protection in photonic systems, such as in photonic crystal slabs, while accounting for in-plane and out-of-plane radiative losses. Our approach relies on the spectral localizer that combines the position and Hamiltonian matrices of the system to draw a real-picture of the system’s topology. This operator-based approach to topology allows us to use an effective Hamiltonian directly derived from the full-wave Maxwell equations after discretization via finite-elements method (FEM), resulting in the full account of all the system’s physical processes. As the spectral FEM-localizer is constructed solely from FEM discretization of the system’s master equation, the proposed framework is applicable to any physical system and is compatible with commonly used FEM software. Moving forward, we anticipate the generality of the method to aid in the topological classification of a broad range of complex physical systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Event-modeled Risk Assessment Using Linked Diagrams

Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is a software tool developed at INL for researching the capabilities of dynamic PRA (Probabilistic Risk Assessment). In order to promote the effective use of dynamic PRA by the general community, EMRALD focuses on the following key aspects: Simplifying the modeling process by providing a structure that corresponds to traditional PRA modeling methods Providing a user interface (UI) that makes it easy for the user to model and visualize complex interactions Allowing the user to couple with other analysis applications such as physics based simulations. This includes one-way communication for most applications and two-way loose coupling for customizable applications Providing the sequence and timing of events that lead to the specified outcomes when calculating results Traditional aspects of components with basic events, fault trees, and event trees are all captured in a dynamic framework of state diagrams, which are displayed.

Prescott, SteveR↗

ERF: Energy Research and Forecasting Model

High performance computing (HPC) architectures have undergone rapid development in recent years. As a result, established software suites face an ever increasing challenge to remain performant on and portable across modern systems. Many of the widely adopted atmospheric modeling codes cannot fully (or in some cases, at all) leverage the acceleration provided by General-Purpose Graphics Processing Units, leaving users of those codes constrained to increasingly limited HPC resources. Energy Research and Forecasting (ERF) is a regional atmospheric modeling code that leverages the latest HPC architectures, whether composed of only Central Processing Units (CPUs) or incorporating GPUs. ERF contains many of the standard discretizations and basic features needed to model general atmospheric dynamics. The modular design of ERF provides a flexible platform for exploring different physics parameterizations and numerical strategies. ERF is built on a state-of-the-art, well-supported, software framework (AMReX) that provides a performance portable interface and ensures ERF's long-term sustainability on next generation computing systems. This paper details the numerical methodology of ERF, presents results for a series of verification/validation cases, and documents ERF's performance on current HPC systems. The roughly 5× speed up of ERF (using GPUs) over Weather Research and Forecasting (CPUs only) for a 3D squall line test case highlights the significance of leveraging GPU acceleration.

17 WIND ENERGY↗