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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Key environmental and production factors for understanding variation in switchgrass chemical attributes

Abstract Switchgrass ( Panicum virgatum L.) is a promising feedstock for bioenergy and bioproducts; however, its inherent variability in chemical attributes creates challenges for uniform conversion efficiencies and product quality. It is necessary to understand the range of variation and factors (i.e., field management, environmental) influencing chemical attributes for process improvement and risk assessment. The objectives of this study were to (1) examine the impact of nitrogen fertilizer application rate, year, and location on switchgrass chemical attributes, (2) examine the relationships among chemical attributes, weather and soil data, and (3) develop models to predict chemical attributes using environmental factors. Switchgrass samples from a field study spanning four locations including upland cultivars, one location including a lowland cultivar, and between three and six harvest years were assessed for glucan, xylan, lignin, volatiles, carbon, nitrogen, and ash concentrations. Using variance estimation, location/cultivar, nitrogen application rate, and year explained 65%–96% of the variation for switchgrass chemical attributes. Location/cultivar × year interaction was a significant factor for all chemical attributes indicating environmental‐based influences. Nitrogen rate was less influential. Production variables and environmental conditions occurring during the switchgrass field trials were used to successfully predict chemical attributes using linear regression models. Upland switchgrass results highlight the complexity in plant responses to growing conditions because all production and environmental variables had strong relationships with one or more chemical attributes. Lowland switchgrass was limited to observations of year‐to‐year environmental variability and nitrogen application rate. All explanatory variable categories were important for lowland switchgrass models but stand age and precipitation relationships were particularly strong. The relationships found in this study can be used to understand spatial and temporal variation in switchgrass chemical attributes. The ability to predict chemical attributes critical for conversion processes in a geospatial/temporal manner would provide state‐of‐the‐art knowledge for risk assessment in the bioenergy and bioproducts industry.

09 BIOMASS FUELS↗
DOE OSTI2018

Rapid Freeform Sheet Metal Forming: Technology Development and System Verification

The objective of this project is to develop a transformational RApid Freeform sheet metal Forming Technology (RAFFT) in an industrial environment, which has the potential to increase manufacturing energy efficiency up to ten times, at a fraction of the cost of conventional technologies. The RAFFT technology is a flexible and energy-efficient process that eliminates the need for having geometry-specific forming dies. The innovation lies in the idea of using the energy resource at the local deformation area which provides greater formability, process control, and process flexibility relative to traditional methods. Double-Sided Incremental Forming (DSIF), the core technology in RAFFT, is a new concept for sheet metal forming. A blank sheet is clamped around its periphery and gradually deformed into a complex 3D freeform part by two strategically aligned stylus-type tools that follow a pre-described toolpath. The two tools, one on each side of the blank, can form a part with sharp features for both concave and convex shapes. Since deformation happens locally, the forming force at any instant is significantly decreased when compared to traditional methods. The key advantages of DSIF are its high process flexibility, high energy-efficiency, low capital investment, and the elimination of the need for massive amounts of die casting and machining. Additionally, the enhanced formability and process flexibility of DSIF can open up design spaces and result in greater weight savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Next-Level Energy Management in Manufacturing: Facility-Level Energy Digital Twin Framework Based on Machine Learning and Automated Data Collection

This research introduces an energy prediction framework at the facility level supported by automated data collection and machine learning models. It investigates whether reducing the prediction time scale allows for applying more complex machine learning techniques and if those techniques improve the prediction accuracy. The primary advantages of this framework lie in its automation of the energy prediction process and its provision of real-time energy data suitable for use in energy dashboards or digital twins. A sitewide dataset was created by combining 15 min energy and daily production data of five shops—assembly, battery, body (electric), body (gas), and paint—from a globally recognized electric vehicle manufacturer. Various machine learning models were evaluated on daily, weekly, and monthly datasets, including, in increasingly complex order: naïve, simple linear regression, net regularized generalized linear regression, principal component regression, k-nearest neighbor, random forest, and Bayesian regularized neural network. Compared to the current state-of-the-art energy consumption prediction for the industrial facility level, this research investigates more complex models and smaller time intervals for higher accuracy. The findings revealed that the more complex monthly models require a minimum of a year and a half of data to operate, while weekly models demand a year of data to achieve improved accuracy. Daily models can operate with only six months of data but exhibit poor performance due to reduced prediction accuracy of production. Key challenges identified include access to reliable, high-quality energy and production data and the initial demand for human labor.

digital twin↗
NASA NTRS2012

Integrated Data Modeling and Simulation on the Joint Polar Satellite System Program

The Joint Polar Satellite System is a modern, large-scale, complex, multi-mission aerospace program, and presents a variety of design, testing and operational challenges due to: (1) System Scope: multi-mission coordination, role, responsibility and accountability challenges stemming from porous/ill-defined system and organizational boundaries (including foreign policy interactions) (2) Degree of Concurrency: design, implementation, integration, verification and operation occurring simultaneously, at multiple scales in the system hierarchy (3) Multi-Decadal Lifecycle: technical obsolesce, reliability and sustainment concerns, including those related to organizational and industrial base. Additionally, these systems tend to become embedded in the broader societal infrastructure, resulting in new system stakeholders with perhaps different preferences (4) Barriers to Effective Communications: process and cultural issues that emerge due to geographic dispersion and as one spans boundaries including gov./contractor, NASA/Other USG, and international relationships.

Roberts, Christopher J.↗
NASA NTRSDate not supplied

Machine Learning to Predict Joint Performance in Epoxy Composites Based on Process Parameters

Polymer matrix composites are gaining popularity in the aerospace industry due to their high specific strength, fatigue properties, and processability. However, based on current FAA certification guidelines, manufacturers utilizing current state-of-the art composites made with adhesive bonds commonly install redundant fasteners to guarantee the strength of these adhesively bonded composite parts.1,2 The number of fasteners in a single-aisle commercial transport aircraft is typically on the order of 105, which reduces manufacturing rate, increases cost tremendously, and reduces the advantage of the specific strength composites provide. Due to this, the Adhesive Free Bonding of Composites (AERoBOND) project at NASA Langley Research Center has developed a novel assembly process to manufacture complex composite parts without the use of adhesives and fasteners.1 However, optimization of the process is currently challenging due to the complex and interdependent process parameters. To assist with the optimization, four machine learning algorithms utilizing gradient boosting decision trees were created to provide predictions for the mechanical and characterization properties of the composite parts. Approximately 200 random states from each algorithm were tested, and the models from each state were isolated and analyzed based on their accuracy, a validation process, and their feature importance. This analysis concluded that the models created from the machine learning algorithms could accelerate a parametric study for the AERoBOND process by rapidly optimizing process parameters to achieve desired performance characteristics.

Brennen M Middleton↗
DOE OSTI2024

Bridging the gap between academic research and industrial development in advanced all-solid-state lithium–sulfur batteries

The energy storage and vehicle industries are heavily investing in advancing all-solid-state batteries to overcome critical limitations in existing liquid electrolyte-based lithium-ion batteries, specifically focusing on mitigating fire hazards and improving energy density. All-solid-state lithium–sulfur batteries (ASSLSBs), featuring earth-abundant sulfur cathodes, high-capacity metallic lithium anodes, and non-flammable solid electrolytes, hold significant promise. Despite these appealing advantages, persistent challenges like sluggish sulfur redox kinetics, lithium metal failure, solid electrolyte degradation, and manufacturing complexities hinder their practical use. Further, to facilitate the transition of these technologies to an industrial scale, bridging the gap between fundamental scientific research and applied R&D activities is crucial. Our review will address the inherent challenges in cell chemistries within ASSLSBs, explore advanced characterization techniques, and delve into innovative cell structure designs. Furthermore, we will provide an overview of the recent trends in R&D and investment activities from both academia and industry. Building on the fundamental understandings and significant progress that has been made thus far, our objective is to motivate the battery community to advance ASSLSBs in a practical direction and propel the industrialized process.

25 ENERGY STORAGE↗
DOE OSTI2024

Enrichable consortia of microbial symbionts degrade macroalgal polysaccharides in Kyphosus fish

ABSTRACT Coastal herbivorous fishes consume macroalgae, which is then degraded by microbes along their digestive tract. However, there is scarce genomic information about the microbiota that perform this degradation. This study explores the potential of Kyphosus gastrointestinal microbial symbionts to collaboratively degrade and ferment polysaccharides from red, green, and brown macroalgae through in silico study of carbohydrate-active enzyme and sulfatase sequences. Recovery of metagenome-assembled genomes (MAGs) from previously described Kyphosus gut metagenomes and newly sequenced bioreactor enrichments reveals differences in enzymatic capabilities between the major microbial taxa in Kyphosus guts. The most versatile of the recovered MAGs were from the Bacteroidota phylum, whose MAGs house enzyme collections able to decompose a variety of algal polysaccharides. Unique enzymes and predicted degradative capacities of genomes from the Bacillota (genus Vallitalea ) and Verrucomicrobiota (order Kiritimatiellales ) highlight the importance of metabolic contributions from multiple phyla to broaden polysaccharide degradation capabilities. Few genomes contain the required enzymes to fully degrade any complex sulfated algal polysaccharide alone. The distribution of suitable enzymes between MAGs originating from different taxa, along with the widespread detection of signal peptides in candidate enzymes, is consistent with cooperative extracellular degradation of these carbohydrates. This study leverages genomic evidence to reveal an untapped diversity at the enzyme and strain level among Kyphosus symbionts and their contributions to macroalgae decomposition. Bioreactor enrichments provide a genomic foundation for degradative and fermentative processes central to translating the knowledge gained from this system to the aquaculture and bioenergy sectors. IMPORTANCE Seaweed has long been considered a promising source of sustainable biomass for bioenergy and aquaculture feed, but scalable industrial methods for decomposing terrestrial compounds can struggle to break down seaweed polysaccharides efficiently due to their unique sulfated structures. Fish of the genus Kyphosus feed on seaweed by leveraging gastrointestinal bacteria to degrade algal polysaccharides into simple sugars. This study reconstructs metagenome-assembled genomes for these gastrointestinal bacteria to enhance our understanding of herbivorous fish digestion and fermentation of algal sugars. Investigations at the gene level identify Kyphosus guts as an untapped source of seaweed-degrading enzymes ripe for further characterization. These discoveries set the stage for future work incorporating marine enzymes and microbial communities in the industrial degradation of algal polysaccharides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Synthetic Metal Atomic Layer Deposition Tool (Final Report)

As part of the Cyclotron Road program, Laminera Inc. worked towards development of atomic layer deposition process customizations and tool modifications to produce synthetic metal films at commercial scale and improve the film quality. Today's state-of-the-art in atomic layer deposited synthetic metal technology is only possible at a research-scale because current tools have practical limitations for scaling industrially and generating high conductivity films. Ultrathin, conformal synthetic metal films have many possible applications such as high surface area nanoporous electrodes for supercapacitors and water desalination devices; protective electrode coatings for electrochemical devices; seed layers for semiconductor device fabrication; or metallic component stabilizing coatings that enable enhanced storage density in next generation hard disk drives. The best synthetic metal conductive and plasmonic properties have been demonstrated using sputtering, which relies on high temperature sputtering with substrate dependent and directional growth limiting usage. This work explored refining process and tool modifications to create ultrathin, conformal, synthetic metal films that can be deposited with high quality over complex three-dimensional surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Success Path Method: Introduction to the Success Path Method Software Tool©

As part of its commitment to advancing safety and reliability assessment methodologies, Argonne National Laboratory pioneered the use of an evaluation method called the Success Path Method (SPM) to improve risk management for offshore oil and gas operations. The development of the SPM at Argonne has been driven by the need to improve existing risk assessment methodologies by focusing on the steps necessary for success rather than failure modes alone. This is particularly important for industrial environments like offshore facilities that perform multiple functions under a continuously evolving set of operational conditions – such as water depth and temperature, currents, and weather conditions. In these dynamic environments, the traditional Probabilistic Risk Assessment (PRA) approach is far too complex as it focuses on what can go wrong – which comprises an infinite failure space that must be fully explored and understood. By shifting the focus to a finite space of success paths, the SPM enables operators and decision makers to prioritize a manageable number of steps that must go right to ensure success. Building on its five decades of experience in safety assessments for the nuclear industry, Argonne made major adaptations to existing risk assessment methods utilizing features similar to fault trees that are traditionally used in PRA to map all pathways in which the system can malfunction. In contrast, SPM identifies the components and processes that must function correctly to achieve specific outcomes – such as preventing the uncontrolled release of hydrocarbons during drilling operations. The SPM framework integrates equipment, procedures, software, processes, and human actions to ensure that physical barriers meet critical safety functions in dynamic operational conditions. This approach helps identify failure modes and improve operational risk management by narrowing the focus to key success elements, which in turn reduces uncertainty and helps users understand, manage, and respond to failures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2001

Reverse Micelle Based Synthesis of Microporous Materials in Microgravity

Microporous materials include a large group of solids of varying chemical composition as well as porosity. These materials are characterized by channels and cavities of molecular dimensions. The framework structure is made up of interconnecting T-O-T' bonds, where T and T' can be Si, Al, P, Ga, Fe, Co, Zn, B and a host of other elements. Materials with Si-O-Al bonding in the framework are called zeolites and are extensively used in many applications. Ion-exchange properties of these materials are exploited in the consumer and environmental industries. Chemical and petroleum industries use zeolites as catalysts in hydrocarbon transform ations. Synthesis of new microporous frameworks has led to the development of new technologies, and thus considerable effort worldwide is expended in their discovery. Microporous materials are typically made under hydrothermal conditions. Influence of nature of starting reactants, structure directing agents, pH, temperature, and aging all have profound influence on the synthesis process. This is primarily because the most interesting open frameworks are not necessarily the stable structures in the reaction medium. Thus, the discovery of new frameworks is often tied to finding the right composition and synthesis conditions that allow for kinetic stabilization of the structure. This complexity of the synthesis process and limited understanding of it has made it difficult to develop directed is of microporous materials and most advances in this field have been made by trial and error. The basic issues in crystal growth of these materials include: (1) Nature of the nucleation process; (2) Molecular structure and assembly of nuclei; (3) Growth of nuclei into crystals; (4) Morphology control; and (5) Transformation of frameworks into other structures. The NASA-funded research described in this paper focuses on all the above issues and has been described in several publications. We present the highlights of our program, especially with the focus on possible experiments in microgravity.

Dutta, Prabir K.↗
NASA NTRS1999

A More Accurate and Efficient Technique Developed for Using Computational Methods to Obtain Helical Traveling-Wave Tube Interaction Impedance

The phenomenal growth of commercial communications has created a great demand for traveling-wave tube (TWT) amplifiers. Although the helix slow-wave circuit remains the mainstay of the TWT industry because of its exceptionally wide bandwidth, until recently it has been impossible to accurately analyze a helical TWT using its exact dimensions because of the complexity of its geometrical structure. For the first time, an accurate three-dimensional helical model was developed that allows accurate prediction of TWT cold-test characteristics including operating frequency, interaction impedance, and attenuation. This computational model, which was developed at the NASA Lewis Research Center, allows TWT designers to obtain a more accurate value of interaction impedance than is possible using experimental methods. Obtaining helical slow-wave circuit interaction impedance is an important part of the design process for a TWT because it is related to the gain and efficiency of the tube. This impedance cannot be measured directly; thus, conventional methods involve perturbing a helical circuit with a cylindrical dielectric rod placed on the central axis of the circuit and obtaining the difference in resonant frequency between the perturbed and unperturbed circuits. A mathematical relationship has been derived between this frequency difference and the interaction impedance (ref. 1). However, because of the complex configuration of the helical circuit, deriving this relationship involves several approximations. In addition, this experimental procedure is time-consuming and expensive, but until recently it was widely accepted as the most accurate means of determining interaction impedance. The advent of an accurate three-dimensional helical circuit model (ref. 2) made it possible for Lewis researchers to fully investigate standard approximations made in deriving the relationship between measured perturbation data and interaction impedance. The most prominent approximations made in the analysis were addressed and fully investigated for their accuracy by using the three-dimensional electromagnetic simulation code MAFIA (Solution of Maxwell's Equations by the Finite Integration Algorithm) (refs. 3 and 4). We found that several approximations introduced significant error (ref. 5).

Kory, Carol L.↗
DOE OSTI2020

NMDQi Nuclear Materials Discovery and Qualification Initiative Conference Overview

The Nuclear Materials Discovery and Qualification Initiative (NMDQi) is designed to accelerate nuclear materials qualification to fulfill the promises of early and advanced reactor technologies as a safe, clean, and low-cost baseload energy. Materials development and qualification in the nuclear industry is by definition challenging due to stringent safety requirements, limited availability of specialized facilities for materials irradiation and testing, and the challenging high-temperature, high-radiation environment. NMDQi will establish tools and capabilities that will greatly accelerate the nuclear fuels and materials development process. These tools will provide both computationally informed insights and high-throughput infrastructure with the goal of completing qualification in a single pass. In this approach, materials must be fabricated with a range of properties of interest so that materials performance can be examined in parallel, rather than with multiple discrete specimens. Advanced manufacturing (AM) techniques, which can produce complex component geometries, microstructures, and compositions, are ideal. The improved process monitoring and control that AM can provide are ideal for ensuring and reducing material variability, which will be particularly important as standards committees pursue regulations for AM components. However, gaining these benefits requires overcoming the substantial barrier of qualifying AM processes and the resulting materials and components for supporting research campaigns and eventually nuclear service.

36 MATERIALS SCIENCE↗
DOE OSTI2017

The Future of Robotics/Remote Handling Solutions for the Nuclear Industry - 17347

The nuclear industry is seeing a resurgence of development and utilization of advanced integrated systems; fused sensor arrays; autonomous, remote and hybrid operations; and augmented reality display and control system interfaces. A new age of 'robotics' and remote handling technologies. For many years the use of robotics in nuclear applications has been done sparingly due to technical limitations, perceived and real reliability issues, perceived and real risk concerns, and cost. Although robotics have been used successfully on a variety of projects globally, the underuse of this technology, particularly within the nuclear industry both public and private, is overwhelming. As the number of complex, high hazard projects in the nuclear industry increases, the use of robotics for maintenance, inspection, repair, decommissioning, and remediation activities will become increasingly vital in the future. The risks associated with direct human exposure are high and thus eliminating the risk, or managing it to acceptable levels by using robotics/remote handling as well as other technologies is critical to success as more extreme environment operations and tasks are undertaken. Recent and ongoing advances in technology now allows us to safely and effectively remove the direct / in-situ human element from these type of activities. All the while delivering the same or better outcomes when considering the alternatives when limited or no direct / in-situ human intervention would be allowed. The biggest obstacles the nuclear industry faces center on the cost, reliability, maintainability, effectiveness and appropriate uses of robotics/remote handling solutions in a nuclear (radiation and/or contamination) environment. In order to mitigate these concerns, a sound approach to the use of robotics needs to be addressed. This approach must include: 1. A better understanding of what technology is available and how it can be utilized across multiple sectors, e.g. Commercial Off-the-Shelf (COTS) technology modified / adapted for the nuclear sector; 2. How to implement technology in an integrated pragmatic approach that is cost effective by combining technological know-how / subject matter expertise (SME) with the equivalent subject matter expertise in regulatory, operational and maintenance requirements and limitations, such that a more complete set of functional and operational requirements can be jointly developed in the process. 3. The integration of requirements (project, site, regulatory, etc.), risk management (human factors) and technology, i.e. a marriage between political, programmatic, and technological factors. As the development of robotic/remote handling technology progresses and the successful implementation on projects is demonstrated, the better off the industry will be. This paper provides an overview of the fundamental issues facing the nuclear industry with regard to effective and successful technology selection, maturation, deployment, and integrated risk management, and offers suggestions on how we may overcome these persistent issues now and in the future. Robotic systems and solution experts that are focused on the integration of proven technologies - and that are an integrated part of the project team from its onset - are a necessity for successful planning during nuclear operations. The approach to nuclear operations should always be, 'what is the simplest, most effective way we can approach a particular project need?'. Understanding and implementing the right technologies is where the true value will be recognized. The integration of systems, which includes more than just robotics, is key when developing schemes for these types of complex operations. Often times during planning, the remote handling needs of the job are set aside to be evaluated at a later time due to risk concerns and lack of knowledge. The issue is, experts in the area of robotics or remote handling are rarely involved in the upfront planning. As a result, unnecessary constraints, risks, and obstacles are imposed on project teams to deliver. If done intelligently, this should be introduced at the forefront of planning. Using this type of sound approach leads to effective task organization for the end user. By developing an overall philosophy that leverages proven technologies with implementation expertise; i.e. solutions versus products, is a recipe for success. This is the area that is under-appreciated in the industry and one that needs to be recognized on a much broader scale. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Hydrotreatment of pyrolysis bio-oil: A review

Fast pyrolysis is an effective process to convert more than 60 wt. % of lignocellulosic materials into a bio-oil that can be further hydrotreated for transportation fuel production. However, bio-oil is acidic, viscous, and chemically unstable due to its high oxygen content. Therefore, increasing attention has being paid to deoxygenation of bio-oil through catalytic hydrotreatment into a “drop-in” fuel has been gaining attention from researchers. The first section of this review is devoted to summarize our current understanding of bio-oil composition. Bio-oil hydrotreatment is typically conducted in two-steps. In the first step, known as stabilization, the reactive carbonyl and carboxyl functional groups are transformed into alcohols at a temperature between 373 and 573 K. In the second step, between 623 and 673 K, cracking and hydro-deoxygenation (HDO) occurs. The most common catalysts used in the stabilization step are noble metals (Pt, Ru, Pd) supported on carbon and metal oxides (TiO2, Al2O3, SiO2, Fe2O3, ZrO2). The most common catalysts for deoxygenation and hydrocracking are sulfided CoMo or NiMo. More recently transition metal phosphides and carbides have been shown to be active. The effect of hydrotreatment parameters and the main global reaction mechanisms are discussed. In the first section, we update the progresses made on bio-oil composition, followed by a detailed discussion on the role of heterogeneous catalysts. Many of the bio-oil hydrotreament studies in the literature are based on model compound results. The reactions revealed by such approach are summarized and discussed. Although these studies provide valuable information for developing upgrading strategies, bio-oil chemistry is difficult to describe by model compounds. Thus, we also reviewed a smaller number of hydrotreatment studies of pyrolysis oil fractions. The presence of several oxygenated functional groups (phenols, carboxylic acids, carbonyls, alcohols) in monomeric and oligomeric molecules is a major challenge to study hydrotreatment reactions. Under realistic industrial operational conditions undesirable polymerization and crosslinking reactions leading to catalyst deactivation are very important. In spite of the extensive work on bio-oil hydrotreatment, the nature of the reactions happening in these complex oils is still poorly known. Pyrolytic lignin and sugars have been identified as important contributors to coke formation. Both fractions can then undergo successful hydrogenation or hydrogenolysis over the catalysts. The review ends with a discussion on future prospects and challenges to hydrotreat pyrolysis oils. Because bio-oil is a liquid formed by hundreds of molecules covering a wide range of molecular weights and functionalities, it is very unlikely that a single hydrotreatment technology that makes a good use of each of its molecules could be found. In fact, current hydrotreatment schemes sacrifice some fractions (convert them into low value products) to maximize the conversion of others into fuel. Separation of bio-oil in fractions and processing of each of them via hydrotreatment or by other suitable technology at optimized conditions with well suited catalysts to obtain high value products seems to be the most promising path to reduce hydrogen consumption, coke formation and enhance the economic viability of bio-oil refineries.

Han, Yinglei↗
NASA NTRS2000

Use Computer-Aided Tools to Parallelize Large CFD Applications

Porting applications to high performance parallel computers is always a challenging task. It is time consuming and costly. With rapid progressing in hardware architectures and increasing complexity of real applications in recent years, the problem becomes even more sever. Today, scalability and high performance are mostly involving handwritten parallel programs using message-passing libraries (e.g. MPI). However, this process is very difficult and often error-prone. The recent reemergence of shared memory parallel (SMP) architectures, such as the cache coherent Non-Uniform Memory Access (ccNUMA) architecture used in the SGI Origin 2000, show good prospects for scaling beyond hundreds of processors. Programming on an SMP is simplified by working in a globally accessible address space. The user can supply compiler directives, such as OpenMP, to parallelize the code. As an industry standard for portable implementation of parallel programs for SMPs, OpenMP is a set of compiler directives and callable runtime library routines that extend Fortran, C and C++ to express shared memory parallelism. It promises an incremental path for parallel conversion of existing software, as well as scalability and performance for a complete rewrite or an entirely new development. Perhaps the main disadvantage of programming with directives is that inserted directives may not necessarily enhance performance. In the worst cases, it can create erroneous results. While vendors have provided tools to perform error-checking and profiling, automation in directive insertion is very limited and often failed on large programs, primarily due to the lack of a thorough enough data dependence analysis. To overcome the deficiency, we have developed a toolkit, CAPO, to automatically insert OpenMP directives in Fortran programs and apply certain degrees of optimization. CAPO is aimed at taking advantage of detailed inter-procedural dependence analysis provided by CAPTools, developed by the University of Greenwich, to reduce potential errors made by users. Earlier tests on NAS Benchmarks and ARC3D have demonstrated good success of this tool. In this study, we have applied CAPO to parallelize three large applications in the area of computational fluid dynamics (CFD): OVERFLOW, TLNS3D and INS3D. These codes are widely used for solving Navier-Stokes equations with complicated boundary conditions and turbulence model in multiple zones. Each one comprises of from 50K to 1,00k lines of FORTRAN77. As an example, CAPO took 77 hours to complete the data dependence analysis of OVERFLOW on a workstation (SGI, 175MHz, R10K processor). A fair amount of effort was spent on correcting false dependencies due to lack of necessary knowledge during the analysis. Even so, CAPO provides an easy way for user to interact with the parallelization process. The OpenMP version was generated within a day after the analysis was completed. Due to sequential algorithms involved, code sections in TLNS3D and INS3D need to be restructured by hand to produce more efficient parallel codes. An included figure shows preliminary test results of the generated OVERFLOW with several test cases in single zone. The MPI data points for the small test case were taken from a handcoded MPI version. As we can see, CAPO's version has achieved 18 fold speed up on 32 nodes of the SGI O2K. For the small test case, it outperformed the MPI version. These results are very encouraging, but further work is needed. For example, although CAPO attempts to place directives on the outer- most parallel loops in an interprocedural framework, it does not insert directives based on the best manual strategy. In particular, it lacks the support of parallelization at the multi-zone level. Future work will emphasize on the development of methodology to work in a multi-zone level and with a hybrid approach. Development of tools to perform more complicated code transformation is also needed.

Jin, H.↗
DOE OSTI2017

Succession in the petroleum reservoir microbiome through an oil field production lifecycle

Subsurface petroleum reservoirs are an important component of the deep biosphere where indigenous microorganisms live under extreme conditions and in isolation from the Earth's surface for millions of years. However, unlike the bulk of the deep biosphere, the petroleum reservoir deep biosphere is subject to extreme anthropogenic perturbation, with the introduction of new electron acceptors, donors and exogenous microbes during oil exploration and production. Despite the fundamental and practical significance of this perturbation, there has never been a systematic evaluation of the ecological changes that occur over the production lifetime of an active offshore petroleum production system. Analysis of the entire Halfdan oil field in the North Sea (32 producing wells in production for 1-15 years) using quantitative PCR, multigenic sequencing, comparative metagenomic and genomic bins reconstruction revealed systematic shifts in microbial community composition and metabolic potential, as well as changing ecological strategies in response to anthropogenic perturbation of the oil field ecosystem, related to length of time in production. The microbial communities were initially dominated by slow growing anaerobes such as members of the Thermotogales and Clostridiales adapted to living on hydrocarbons and complex refractory organic matter. However, as seawater and nitrate injection (used for secondary oil production) delivered oxidants, the microbial community composition progressively changed to fast growing opportunists such as members of the Deferribacteres, Delta-, Epsilon- and Gammaproteobacteria, with energetically more favorable metabolism (for example, nitrate reduction, H2S, sulfide and sulfur oxidation). This perturbation has profound consequences for understanding the microbial ecology of the system and is of considerable practical importance as it promotes detrimental processes such as reservoir souring and metal corrosion. These findings provide a new conceptual framework for understanding the petroleum reservoir biosphere and have consequences for developing strategies to manage microbiological problems in the oil industry.

02 PETROLEUM↗
DOE OSTI2019

Resolving Local Configurational Contributions to X-ray and Neutron Radial Distribution Functions Within Solutions of Concentrated Electrolytes – A Case Study of Concentrated NaOH

Extreme conditions of complex materials often lead to a manifold of local environments that challenge characterization and require new advances at the intersection of modern experimental and theoretical techniques. In this contribution, highly caustic and viscous aqueous NaOD solutions were characterized with a combination of X-ray and neutron radial distribution function (RDF) analyses, molecular dynamics simulations and sub-ensemble analysis. The interpretation of the experimental RDFs extends beyond the traditional understanding of atom-pair interactions and to the individual contributions of specific molecular-scale configurations (below 3.5 Å). This integrated approach yields unique insight into the complex and significant breath of ion solvation and pairing structural motifs present, the experimental sensitivity of RDFs to changes in local geometries, and the challenge of experimentally differentiating the ensemble of all superimposed local environments — a feature of increasing importance within the extreme condition of high ionic strength. This study was facilitated by the development of a chemically resistant sample cell for in-situ neutron total scattering measurements of highly caustic materials at elevated temperature and pressure conditions. Advancing these integrated capabilities is critical for ongoing model validation efforts and for extending the predictive capabilities needed for the extremes of chemical composition, aiding a variety of industrial processes that include advanced nuclear waste remediation and metal refining strategies.

Semrouni, David↗
DOE OSTI2023

Carbonate-Catalyzed CO 2 Insertion into Hydrocarbon C-H Bonds (Final Technical Report)

The development of methods to utilize CO 2 as a feedstock for chemical and fuel synthesis is critical for creating renewable alternatives to fossil fuel-based products. This project investigated a class of catalyst materials known as "dispersed carbonates", which are composed of alkali carbonate salts (e.g. potassium carbonate) dispersed in porous support materials. These catalysts react with CO 2 and organic molecules to form chemicals known as carboxylates that have wide applications in the chemical industry. The project used a combination of spectroscopic and reactivity studies to provide fundamental insight into the structure and mechanism of dispersed carbonates in these reactions, leading to variants with greater reactivity. In addition, dispersed carbonates were investigated for CO 2 hydrogenation catalysis, which is critical for processes under development for making sustainable fuels. The dispersed carbonates proved to be highly active and selective catalysts for the reverse water gas shift reaction in which CO 2 is hydrogenated to CO. The dispersed carbonates provide a compelling alternative to conventional metal-based catalysts for reverse water gas shift that could enable new process designs with higher efficiency and lower complexity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗