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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

ADAPTIVE SURROGATES WITHIN THE RAVEN FRAMEWORK FOR DYNAMIC PROBABILISTIC RISK ASSESSMENT ANALYSIS

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment (PRA), Uncertainty Quantification (UQ), data mining analysis and optimization studies. RAVEN has demonstrated a good level of maturity in terms of state-of-art and advanced analysis methodologies. In the past year the RAVEN code has been released as open-source project and is available to download (raven.inl.gov) free of charge. The main subject of this paper is to present a new system within the RAVEN framework to drastically accelerate PRA and UQ analysis using acceleration schemes based on surrogate modeling. This system is based on the heavy usage of surrogate modeling and artificial intelligence algorithms, able to emulate the response of a physical system in closed domains (domains where the surrogate models have been constructed from). The aim of this paper is to show to the community how the employment of surrogate modeling techniques can be a viable solution for the current and future challenges in terms of PRA, UQ and Safety Margins characterizations. In addition, in this manuscript it is presented the construction of a RAVEN new entity named “HybridModel” that is aimed to switch between a high-fidelity code and its linked surrogate, accelerating the PRA and UQ processes without largely reducing the accuracy of the results of the analyses. All these new capabilities will be shown with an application example about a Station Black Out scenario for a prototypical Pressurized Water Reactor (modeled with RELAP5-3D).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Updating the U.S. Life Cycle GHG Petroleum Baseline to 2014 with Projections to 2040 Using Open-Source Engineering-Based Models

Here, the National Energy Technology Laboratory produced a well-to-wheels (WTW) life cycle greenhouse gas analysis of petroleum-based fuels consumed in the U.S. in 2005, known as the NETL 2005 Petroleum Baseline. This study uses a set of engineering-based, open-source models combined with publicly available data to calculate baseline results for 2014. An increase between the 2005 baseline and the 2014 results presented here (e.g., 92.4 vs 96.2 g CO 2 e/MJ gasoline, + 4.1%) are due to changes both in modeling platform and in the U.S. petroleum sector. An updated result for 2005 was calculated to minimize the effect of the change in modeling platform, and emissions for gasoline in 2014 were about 2% lower than in 2005 (98.1 vs 96.2 g CO 2 e/MJ gasoline). The same methods were utilized to forecast emissions from fuels out to 2040, indicating maximum changes from the 2014 gasoline result between +2.1% and –1.4%. The changing baseline values lead to potential compliance challenges with frameworks such as the Energy Independence and Security Act (EISA) Section 526, which states that Federal agencies should not purchase alternative fuels unless their life cycle GHG emissions are less than those of conventionally produced, petroleum-derived fuels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Framework for Analysis and Visualization of Simulation Data (VizAly)

As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the cosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational data sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing platforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.

Wendelberger, Joanne↗
DOE OSTI2018

Mapping Benthic Habitat Conditions and Seafloor Deposits using Sediment Profile Imaging and a Semiautomated Image Processing System

Objectives/Scope: Sediment profile imaging (SPI) technology characterizes in situ physical, geochemical, and biological seafloor features. SPI was required by Mexico’s Agency for Safety, Energy, and Environment in 2017 for environmental baseline surveys (EBS) of oil lease blocks in the southern Gulf of Mexico. Because of its ability to provide information on benthic community health and the distribution of very thin (down to the centimeter scale) layers of deposited materials, SPI technology is highly effective for mapping drill cuttings or drilling muds released around wellheads during exploration or production and documenting their ecological impacts. SPI technology has not been widely used in the oil and gas industry for EBS or other monitoring activities. A primary objective of this work is to improve the transparency and consistency of the SPI data generation and data management process. Methods, Procedures, Process: The SPI camera works like an inverted periscope and obtains an undisturbed 21x15-cm cross-sectional image of the upper sediment column. The camera is internally powered and can be deployed rapidly from a standard winch in depths to 4,000 m. Many stations can be sampled in a single day by “pogo-sticking” across a survey area. Sediment grain size, penetration depth, surface boundary roughness, natural and anthropogenic depositional layers, depth of the oxidized surface sediment layer, maximum biogenic mixing depth, and infaunal successional stage can be directly measured at sea or immediately following the cruise. Final SPI data sets can be provided within a few weeks of the survey. Results, Observations, Conclusions: Details on the features measured in SPI images and the underlying interpretive paradigms are presented. To standardize the SPI data generation process, Integral Consulting Inc. has developed 1) a semiautomated image analysis platform, and 2) a SPI data-specific database architecture that allows both numerical and non-numerical metrics to be incorporated into a standard database structure. An integrated, software-based SPI analysis platform has been developed that imports image files and metadata and provides a graphical user interface. The software automatically stores the data, which can then be reviewed for quality assurance, plotted, statistically analyzed, and mapped or exported to other platforms (e.g., Esri ArcGIS©) for further evaluation. Image processing algorithms have been developed using a combination of open-source and commercially available software packages (e.g., MATLAB® and OpenCV) to automatically quantify key parameters. Novel/Additive Information: SPI technology’s underutilization in the oil and gas industry may be in part due to a lack of standardization in the measurement of basic features in SPI images. A primary objective of this work is to develop a streamlined, standardized, and transparent process for generating and managing SPI data.

02 PETROLEUM↗
DOE OSTI2022

Slow control and data acquisition development in the Mu2e experiment

The muon campus program at Fermilab includes the Mu2e experiment that will search for a charged-lepton flavor violating processes where a negative muon converts into an electron in the field of an aluminum nucleus, improving by four orders of magnitude the search sensitivity reached so far.Mu2e’s Trigger and Data Acquisition System (TDAQ) uses {\it otsdaq} solution. Developed at Fermilab, {\it otsdaq} uses the {\it artdaq} DAQ framework and {\it art} analysis framework, for event transfer, filtering, and processing.{\it otsdaq} is an online DAQ software suite with a focus on flexibility and scalability, and provides a multi-user interface accessible through a web browser.A Detector Control System (DCS) for monitoring, controlling, alarming, and archiving has been developed using the Experimental Physics and Industrial Control System (EPICS) open source Platform. The DCS System has also been integrated into {\it otsdaq}, providing a GUI multi-user, web-based control, and monitoring dashboard.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

NBIC Biofeeds: Deploying a New, Digital Tool for Open Source Biosurveillance across Federal Agencies

The National Biosurveillance Integration Center (NBIC) is deploying a scalable, flexible open source data collection, analysis, and dissemination tool to support biosurveillance operations by the U.S. Department of Homeland Security (DHS) and its federal interagency partners.IntroductionNBIC integrates, analyzes, and distributes key information about health and disease events to help ensure the nation’s responses are well-informed, save lives, and minimize economic impact. To meet its mission objectives, NBIC utilizes a variety of data sets, including open source information, to provide comprehensive coverage of biological events occurring across the globe. NBIC Biofeeds is a digital tool designed to improve the efficiency of analyzing large volumes of open source reporting and increase the number of relevant insights gleaned from this dataset. Moreover, the tool provides a mechanism to disseminate tailored, electronic message notifications in near-real time so that NBIC can share specific information of interest to its interagency partners in a timely manner. NBIC intends to implement operational use of the capability in FY 2018. The core components of the system are data collection, curation, and dissemination of information deemed important by NBIC subject matter experts. NBIC Biofeeds has captured information from more than 70,000 unique sources published from around the globe and presents, on average, 9,000 new biosurveillance-relevant articles to users each day. NBIC leverages a variety of data feeds, including third party aggregators like Google and subscription-based feeds such as HealthMap, as well as Really Simple Syndication (RSS) feeds and web-scraping of highly relevant sources. The NBIC biosurveillance taxonomy imbedded in the tool consists of more than 600 metadata targets that cover key information for understanding the significance of an active biological event, including etiologic agents, impact to humans and animals (e.g., infection severity, healthcare workers involved, type of host), social disruption, infrastructure strain, countermeasures engaged, and ‘red flag’ characteristics (e.g., pathogen appearance in a new geographic area, unusual clinical signs). This taxonomy serves as a foundation for data curation and can be tailored by NBIC partners to more directly meet their own mission objectives. At this time, metadata is predominately captured by NBIC analysts, who manually tag information, which triggers the population of three automatically-disseminated products from the tool: 1) the NBIC Daily Biosurveillance Review, 2) immediate and daily summary email notifications, and 3) custom-designed RSS feeds. These products are meant for individual recipients in the federal interagency and for consumption by other biosurveillance information technology systems, such as the Department of Defense, Defense Threat Reduction Agency (DTRA) Biosurveillance Ecosystem (BSVE). NBIC is working in partnership with DTRA to integrate NBIC Biofeeds as an application directly into the BSVE and further develop the BSVE as an all-in-one platform for biosurveillance data analytics. To improve the efficiency and effectiveness of gaining insights using NBIC Biofeeds, developers of the tool at the Pacific Northwest National Laboratory (PNNL) are researching and testing a variety of advanced analytics techniques focused on: 1) article relevancy ratings to improve the review of queried data, 2) significance ratings to elucidate the perceived severity of an event based on reported characteristics, 3) full-text article retrieval and storage for improved machine-tagging, and 4) anomaly detection for emerging threats. Testing and implementation of new analytic capabilities in NBIC Biofeeds is planned for this fiscal year. NBIC Biofeeds was developed to serve as a sophisticated and powerful open source biosurveillance technology of value to the federal government by providing information to stakeholders conducting open source biosurveillance as well as those consuming biosurveillance information. In FY 2018, NBIC Biofeeds will begin operational use by NBIC and an initial set of users in various federal agencies. User accounts for testing purposes will be available to other federal partners, and a broad scope of federal stakeholders can receive products directly from NBIC Biofeeds based on their interests. NBIC Biofeeds is expected to enable more rapid recognition and enhanced analysis of emerging biological events by NBIC analysts. NBIC anticipates other federal agencies with biosurveillance missions will find this technology of value and intends to offer use of the platform to those federal partners that can benefit from access to the tool and information generated from NBIC Biofeeds.

NBIC↗
DOE OSTI2021

Integration of Open-Source URBANopt and Dragonfly Energy Modeling Capabilities into Practitioner Workflows for District-Scale Planning and Design

High-performance districts and communities offer opportunities for reducing energy use, emissions, and costs, and can be instrumental in helping cities achieve their climate goals. The design of such communities requires identification of opportunities early on and their re-evaluation throughout the planning process. There is a need for energy modeling tools that connect 3D Computer-Aided Design (CAD) platforms to simulation engines, enabling detailed energy analysis of districts within the workflows and tools used by practitioners. This paper introduces the Dragonfly and URBANoptTM combined toolset that supports the creation of urban models from a range of geometry formats typically used by designers and planners, and provides an integrated pathway to simulate district-scale energy systems. The toolset is piloted by a global architecture and master planning firm to evaluate several key urban-scale technical questions for the design of a district in Chicago. The findings indicate that, while energy savings can be achieved through traditional architectural studies and enhancements to individual building efficiency, the modeling toolset helps identify additional savings and insights that can be achieved when considering district-scale energy systems. Finally, this study demonstrates how the Dragonfly/URBANopt toolset can integrate with master planning workflows, thereby enabling an iterative performance-based design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Experimental Definition and Validation of Protein Coding Transcripts in Chlamydomonas reinhardtii

Algal fuel sources promise unsurpassed yields in a carbon neutral manner that minimizes resource competition between agriculture and fuel crops. Many challenges must be addressed before algal biofuels can be accepted as a component of the fossil fuel replacement strategy. One significant challenge is that the cost of algal fuel production must become competitive with existing fuel alternatives. Algal biofuel production presents the opportunity to fine-tune microbial metabolic machinery for an optimal blend of biomass constituents and desired fuel molecules. Genome-scale model-driven algal metabolic design promises to facilitate both goals by directing the utilization of metabolites in the complex, interconnected metabolic networks to optimize production of the compounds of interest. Using Chlamydomonas reinhardtii as a model, we developed a systems-level methodology bridging metabolic network reconstruction with annotation and experimental verification of enzyme encoding open reading frames. We reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology. Our approach to generate a predictive metabolic model integrated with cloned open reading frames, provides a cost-effective platform to generate metabolic engineering resources. While the generated resources are specific to algal systems, the approach that we have developed is not specific to algae and can be readily expanded to other microbial systems as well as higher plants and animals.

09 BIOMASS FUELS↗
DOE OSTI2023

Multiparametric optical label-free imaging to analyze plant cell wall assembly and metabolism. (Final Report)

Plant tissues are often considered not ideal for fluorescence imaging because of the pervasive intrinsic fluorescence of many plant metabolites and the intricate interactions with light of the many semi-crystalline polymers at the cell wall. Our project aims to take advantage of this observed shortcoming by developing a label-free, optical microscopy platform for characterizing multiple fingerprints of important cell wall components and stress-related, at subcellular scale resolution. The new imaging system can collect fingerprints from both emitted and scattered light that can inform on the chemical nature, subcellular distribution, anisotropy, and molecular environment of multiple cell wall components in intact plant tissues. We are combining these imaging capabilities with computational tools that enable correlated registration, integration, and analysis. This fully integrated, multiparametric optical system will be used to address biological problems connected to cell wall assembly in grasses. This includes a focus on developmental and environmental variation of cell wall impregnation with silica, lignin, suberin, and cutin in different tissues and cell types. Our research plan comprises three main goals: (1) To develop an accessible imaging platform and associated open-source software able to extract and integrate fingerprints from fluorescence-associated (multispectral emission, lifetime, and polarization), wide-field polarimetry, second harmonic generation (SHG), and stimulated Raman scattering signals (SRS); (2) To determine unique combination of fingerprints for various cell wall components and selected metabolites; (3) To analyze the process of cell wall silicification in grasses and determine how silicification affects cell wall properties and lignin, cutin, and suberin deposition in other cell types under differ stress conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Survey of Use Cases and Scenarios on the Open Energy Data Initiative Solar Systems Integration (OEDI SI) Platform

The Open Energy Data Initiative Solar Systems Integration (OEDI SI) Data and Modeling Platform offers a comprehensive set of use cases tailored for power systems analysis. Each use case is centered around a specific power system analysis problem, supported by composite input data and reference algorithms. These composite input datasets are meticulously assembled using OEDI SI's data preprocessing tools, which integrate raw data from various sources. The primary objectives of the OEDI SI Platform include facilitating access to composite input data through widely accepted input/output formats and verified results. This accessibility enables power system network researchers and developers to validate their algorithms and showcase their applications' capabilities to the broader community. Moreover, the platform strives to promote reproducible, robust, replicable, and generalizable solar systems integration research.

14 SOLAR ENERGY↗
DOE OSTI2025

Predicting Trends in VOC Through Rapid, Multimodal Characterization of State-of-the-Art p-i-n Perovskite Devices

Perovskite photovoltaic technologies are approaching commercial deployment, yet single junction and tandem architectures both still have significant room to improve power conversion efficiency and stability. The ability to perform rapid screening of material quality after altering processing conditions is critical to accelerating the optimization and commercialization of perovskite-based technologies. Currently, researchers utilize a wide range of stand-alone metrology tools to isolate sources of power loss throughout a device stack, which can be slow and labor intensive. Here, we demonstrate the use of a multimodal metrology approach to rapidly determine the maximum achievable and predicted open circuit voltages of >100 perovskite devices during fabrication. Acquisition of these different data is facilitated by combining them into a single integrated measurement platform. We show that these data and automated analysis can be used to rapidly understand and ultimately predict quantitative trends in open circuit voltages of state-of-the-art device architectures. The data and automated analysis workflow presented provides a reliable approach to quickly identify absorber and charge transport layer combinations that can lead to improved open circuit voltages.

14 SOLAR ENERGY↗
DOE OSTI2021

Bioinformatic Teaching Resources – For Educators, by Educators – Using KBase, a Free, User-Friendly, Open Source Platform

Over the past year, biology educators and staff at the U.S. Department of Energy Systems Biology Knowledgebase (KBase) initiated a collaborative effort to develop a curriculum for bioinformatics education. KBase is a free web-based platform where anyone can conduct sophisticated and reproducible bioinformatic analyses via a graphical user interface. Here, we demonstrate the utility of KBase as a platform for bioinformatics education, and present a set of modular, adaptable, and customizable instructional units for teaching concepts in Genomics, Metagenomics, Pangenomics, and Phylogenetics. Each module contains teaching resources, publicly available data, analysis tools, and Markdown capability, enabling instructors to modify the lesson as appropriate for their specific course. We present initial student survey data on the effectiveness of using KBase for teaching bioinformatic concepts, provide an example case study, and detail the utility of the platform from an instructor’s perspective. Even as in-person teaching returns, KBase will continue to work with instructors, supporting the development of new active learning curriculum modules. For anyone utilizing the platform, the growing KBase Educators Organization provides an educators network, accompanied by community-sourced guidelines, instructional templates, and peer support, for instructors wishing to use KBase within a classroom at any educational level–whether virtual or in-person.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗
DOE OSTI2018

Scanning A uger spectromicroscopy using the S cope F oundry software platform

We have developed an open‐source, Python‐based software platform called ScopeFoundry for performing complex, multidimensional microscopy experiments that integrate diverse types of experimental hardware. ScopeFoundry streamlines experiment development by providing a modular environment where hardware controls and measurement schemes can be arranged and customized. Important software tasks such as data management and user interface generation are automated. Using this platform, we have implemented scanning Auger spectromicroscopy on a modified commercial surface analysis system. Spectromicroscopy produces multidimensional datasets with complete spectra at each image pixel, allowing for detailed analysis of material phases where Auger peaks may change in shape and position. Analysis of the surface phases of an advanced electron emission dispenser cathode is presented as an example. We describe the general ScopeFoundry platform, its application to Auger spectromicroscopy, and ways it can be applied to advance surface analysis and microscopy.

Durham, Daniel B.↗
DOE OSTI2017

Simulated impedance of diffusion in porous media

This paper describes the use of a frequency domain, finite-difference scheme to simulate the impedance spectra of diffusion in porous microstructures. We investigate both open and closed systems for a range of ideal geometries, as well as some randomly generated synthetic volumes and tomographically derived microstructural data. In many cases, the spectra deviate significantly from the conventional Warburg-type elements typically used to represent diffusion in equivalent circuit analysis. Furthermore, a key finding is that certain microstructures show multiple peaks in the complex plane, which may be misinterpreted as separate electrochemical processes in real impedance data. This is relevant to battery electrode design as the techniques for nano-scale fabrication become more widespread. This simulation tool is provided as an open-source MatLab application and is freely available online as part of the TauFactor platform.

36 MATERIALS SCIENCE↗
DOE OSTI2016

ADMS State of the Industry and Gap Analysis

An Advanced distribution management system (ADMS) is a platform for optimized distribution system operational management. This platform comprises of distribution management system (DMS) applications, supervisory control and data acquisition (SCADA), outage management system (OMS), and distributed energy resource management system (DERMS). One of the primary objectives of this work is to study and analyze several ADMS component and auxiliary systems. All the important component and auxiliary systems, SCADA, GISs, DMSs, AMRs/AMIs, OMSs, and DERMS, are discussed in this report. Their current generation technologies are analyzed, and their integration (or evolution) with an ADMS technology is discussed. An ADMS technology state of the art and gap analysis is also presented. There are two technical gaps observed. The integration challenge between the component operational systems is the single largest challenge for ADMS design and deployment. Another significant challenge noted is concerning essential ADMS applications, for instance, fault location, isolation, and service restoration (FLISR), volt-var optimization (VVO), etc. There are a relatively small number of ADMS application developers as ADMS software platform is not open source. There is another critical gap and while not being technical in nature (when compared the two above) is still important to consider. The data models currently residing in utility GIS systems are either incomplete or inaccurate or both. This data is essential for planning and operations because it is typically one of the primary sources from which power system model are created. To achieve the full potential of ADMS, the ability to execute acute Power Flow solution is an important pre-requisite. These critical gaps are hindering wider Utility adoption of an ADMS technology. The development of an open architecture platform can eliminate many of these barriers and also aid seamless integration of distribution Utility legacy systems with an ADMS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Hydrodynamic conditions in laser irradiated buried layer experiments

The calculation of open shell ionization level and radiative properties of materials in Non-Local Thermal Equilibrium (NLTE) is currently still a major challenge for any atomic model. The predictions of various NLTE atomic codes at these conditions still differ significantly. In recent years, a new buried layer platform was developed at the Lawrence Livermore National Laboratory and the Laboratory for Laser Energetics. This platform is used to measure ionization distribution and emission of open L-shell, mid-Z ions and open M-shell, high-Z ions at NLTE conditions that are relevant in many laser plasma applications. These experiments offer a unique chance for benchmarking the atomic models. In order to perform these experiments, a uniform well characterized plasma source is required. In this work, we present one-dimensional (1D) and two-dimensional simulations of the experimental platform. These simulations were used for both the design and the analysis of the experiments. The simulations demonstrate the different phases of hydrodynamic evolution of the target and identify the time windows in which uniform conditions can be achieved. A 1D expansion of the target was found to be adequate to describe the target's evolution for most of the experiment duration. The fast 1D simulations were compared with recent experimental results from the Omega laser facility. The sensitivity of the results to several modeling parameters such as the electron flux limiter and laser resonant absorption is reported.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗