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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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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Improving and Assessing Planet Sensitivity of the GPI Exoplanet Survey with a Forward Model Matched Filter

We present a new matched-filter algorithm for direct detection of point sources in the immediate vicinity of bright stars. The stellar point-spread function (PSF) is first subtracted using a Karhunen-Loéve image processing (KLIP) algorithm with angular and spectral differential imaging (ADI and SDI). The KLIP-induced distortion of the astrophysical signal is included in the matched-filter template by computing a forward model of the PSF at every position in the image. To optimize the performance of the algorithm, we conduct extensive planet injection and recovery tests and tune the exoplanet spectra template and KLIP reduction aggressiveness to maximize the signal-to-noise ratio (S/N) of the recovered planets. We show that only two spectral templates are necessary to recover any young Jovian exoplanets with minimal S/N loss. We also developed a complete pipeline for the automated detection of point-source candidates, the calculation of receiver operating characteristics (ROC), contrast curves based on false positives, and completeness contours. We process in a uniform manner more than 330 data sets from the Gemini Planet Imager Exoplanet Survey and assess GPI typical sensitivity as a function of the star and the hypothetical companion spectral type. This work allows for the first time a comparison of different detection algorithms at a survey scale accounting for both planet completeness and false-positive rate. We show that the new forward model matched filter allows the detection of 50% fainter objects than a conventional cross-correlation technique with a Gaussian PSF template for the same false-positive rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology

In this work, we describe the Dark Energy Survey (DES) photometric data set assembled from the first three years of science operations to support DES Year 3 cosmologic analyses, and provide usage notes aimed at the broad astrophysics community. Y3 GOLD improves on previous releases from DES, Y1 GOLD, and Data Release 1 (DES DR1), presenting an expanded and curated data set that incorporates algorithmic developments in image detrending and processing, photometric calibration, and object classification. Y3 GOLD comprises nearly 5000 deg 2 of grizY imaging in the south Galactic cap, including nearly 390 million objects, with depth reaching a signal-to-noise ratio ~10 for extended objects up to iAB ~ 23.0, and top-of-the-atmosphere photometric uniformity <3 mmag. Compared to DR1, photometric residuals with respect to Gaia are reduced by 50%, and per-object chromatic corrections are introduced. Y3 GOLD augments DES DR1 with simultaneous fits to multi-epoch photometry for more robust galactic color measurements and corresponding photometric redshift estimates. Y3 GOLD features improved morphological star–galaxy classification with efficiency >98% and purity >99% for galaxies with 19 < i AB < 22.5. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used to select the cosmologic analysis samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Sandia MEMS Visualization Tools v. 3.0

This is a revision to the Sandia MEMS Visualization Tools. It replaces all previous versions. New features in this version: Support for AutoCAD 2014 and 2015 . This CD contains an integrated set of electronic files that: a) Provides a 2D Process Visualizer that generates cross-section images of devices constructed using the SUMMiT V fabrication process. b) Provides a 3D Visualizer that generates 3D images of devices constructed using the SUMMiT V fabrication process. c) Provides a MEMS 3D Model generator that creates 3D solid models of devices constructed using the SUMMiT V fabrication process. While there exists some files on the CD that are used in conjunction with software package AutoCAD , these files are not intended for use independent of the CD. Note that the customer must purchase his/her own copy of AutoCAD to use with these files.

Yarberry, Victor↗
DOE OSTI2017

Bellerophon Environment for Analysis of Materials (BEAM)

Improvements in scientific instrumentation allow imaging at mesoscopic to atomic length scales, many spectroscopic modes, and now--with the rise of multimodal acquisition systems and the associated processing capability--the era of multidimensional, informationally dense data sets has arrived. Technical issues in these combinatorial scientific fields are exacerbated by computational challenges best summarized as a necessity for drastic improvement in the capability to transfer, store, and analyze large volumes of data. The Bellerophon Environment for Analysis of Materials (BEAM) platform provides material scientists the capability to directly leverage the integrated computational and analytical power of High Performance Computing (HPC) to perform scalable data analysis and simulation and manage uploaded data files via an intuitive, cross-platform client user interface. This framework delivers authenticated, "push-button" execution of complex user workflows that deploy data analysis algorithms and computational simulations utilizing compute-and-data cloud infrastructures and HPC environments like Titan at the Oak Ridge Leadershp Computing Facility (OLCF).

Lingerfelt, Eric J↗
DOE OSTI2021

Flexible and Adaptive Malware Identification Using Techniques from Biology

The holy grail in cyber analytics is to find new ways to understand the information we already have access to. One way to do that is to characterize the data into reasonable sizes and then leverage any known information to generate new insights. Biologists have been using a similar process for decades. This paper introduces the MLSTONES tool set that was developed by leveraging biology and bioinformatics, high performance computing, and statistical algorithms applied to cyber data and specifically to malware. Furthermore, the paper discusses the tool suite, its applications, and how it compares or can work with other related tools.

Peterson, Elena S.↗
DOE OSTI2021

Metals and methylotrophy: Via global gene expression studies

A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. By ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.

Johnson, Zachary J.↗
DOE OSTI2023

A 4 x 4 SiPM Sensor Array with Fast Preamplified Output Engineered for the PWO Detectors of the EIC EEEMCAL

The PbWO4 scintillation detectors for the Electron-Ion Collider Electron Endcap Electromagnetic Calorimeter (EEEMCAL) cannot use vacuum photomultipler tubes due to the high magnetic field environment. We are presenting a readout solution with a 4 x 4 SiPM array directly coupled to a preamplification and summing stage. A second amplification stage with variable gain and offset adjustments is also included in the compact electronics module. The integrated power supply feeds the signal processing chain and the adjustable bias control. The parameter settings are saved locally on a EEPROM and are adjustable via the integrated communication interface through USB or RS485. The design was optimized to maximize signal collection energy resolution, for fast timing and wide dynamic range while keeping a small footprint with low power consumption and heat dissipation. The output response is fast enough to meet the 100 ? 200 ns digitization gate requirements for the detector. The electronics assembly requires no active cooling and includes a temperature sensor and a gain compensation of thermal variations which are important features for stable operation in large scale detector structures. A detector prototype was constructed with 20 mm x 20 mm x 200 mm PWO crystals affixed with individual SiPM array readouts and arranged in a 3 x 3 array. This detector was tested at the Thomas Jefferson National Accelerator Facility with 5GeV positrons. We will present the results of these detector characterization measurements.

Philip, O.↗
DOE OSTI2015

The Acoustic Emission signal acquired by the microphones placed in the CABRI test device along the fourteen last R.I.A. experiments: an example of reproducible research in nuclear science

The CABRI facility is an experimental nuclear reactor of the French Atomic Energy Commission. It is located at the Cadarache Research Centre in southern France and it is designed to act as a support to the French nuclear infrastructure. The purpose of the new testing programme termed, 'CABRI International Programme' (CIP) is to study the behaviour of PWR-type fuel rods at high burnup, equipped with an 'advanced' cladding, under Reactivity Initiated Accident (RIA) conditions (such as the scenario of a control rod ejection). Within the framework of this programme, piloted and funded by the French Institute of Nuclear Radioprotection and Safety (IRSN), ten tests are to be conducted with a frequency of two tests per year. The LPRE laboratory of the CEA which is in charge of the Preparation, realisation and breakdown of the test results studies the possibility to set up a new test analysis based on the processing of signals coming from sensors placed within the test equipment. During the experimental phase, the behaviour of the fuel element generates acoustic waves which can be detected by two microphones placed upstream and downstream of the test device. Studies showed the interest to realize temporal and spectral analyses on these signals by showing the existence of signatures which can be correlated with physical phenomena as the rod failure or the test shutdown (i.e. scram). The work presented in this article results from the will to consolidate these studies. Since the main phenomenon to be tracked is the fuel rod failure, the aim would be to highlight specific events which would have been precursors of the rod failure in order to use in the future these signals for further interpretation. Such an antecedent works resumption leads to a better understanding of the experimental needs and constitutes a good initial state to prepare the new very fast digital data acquisition systems. Although all the raw data are accessible in the form of text files, analyses and graphics representations were not straightforward to reproduce from the ancient studies since that, on one hand, people who were in charge of the original work left the laboratory and on the other hand because it is not easy when the time passes, even with our own work, to be able to remember the steps of data manipulations and the exact setup: - During the ancient experiments the use of analog data acquisition systems required to digitize tapes to be able to realize computer treatments. That had had for consequence to lose the initial dating. This one must be correctly edited to do temporal comparisons. - Analyses require functions for calculations whose parameters has to be well-known to reach the same results. We thus wished to manage our workflow in the idea that it can be easily reproducible on all the experiments. The object of the work presented in this article was to put in practice this strong bind between the data, treatments and generation of the document in order not to hesitate to do the iteration principle in action. We do not have to be afraid by the data driven analyses. According to the philosophy of the literate programming, the text of the technical document is woven with the computer code that produces all the printed output as tables, graphs for the study eliminating hence the unrealistic cut and paste. This difficulty is not specific to the nuclear domain. For many years, researchers have been worked out solutions to this mundane issue. And, presently, new technologies and high-level programming languages offer us actual answers. We will firstly present the tools applied in our laboratory to implement this workflow, then we will describe the global perception carried out to continue the study of the Acoustic Emission signals recorded by the two microphones during the fourteen last CABRI R.I.A. test.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

A Practical Application of Integrated Systems Engineering and Project Management on a Complex EPC Project - 17207

This paper introduces how an integrated set of Systems Engineering (SE) and Project Management (PM) processes were applied in a practical way, to address the challenges on a complex, highly technical, Engineering Procurement Construction project within the nuclear field. This approach was inspired by: - the principles contained in a Community of Practice on Lean in Program Management jointly established in May 2012 by MIT, PMI and INCOSE; - an opportunity to apply international standard ISO/IEC 15288:2008(E) Systems and software engineering - System life cycle processes on a real-life situation; - and the belief that there is great value in applying Systems Engineering and Project Management in an integrated manner on a project. The project offering this opportunity was the Detail Engineering, Procurement, Construction and Cold Commissioning (EPC) of the Silo Direct-encapsulation Plant (SDP). This project was undertaken by the Joint Venture (JV) formed by Areva, Mace and Atkins (a.m.a. Nuclear Ltd). Unfortunately, early termination of the project, at a stage when only a part of the processes and tools were being implemented, did not allow this integrated approach to be demonstrated in full. However, the benefits achieved in the early stages in aligning and forming an integrated project execution team, showed potential for great benefits. This paper covers an introductory analysis of the situation, the successes and benefits achieved from implementing an integrated SE - PM approach up to the stage when the project was terminated, and possible path forward had the project continued. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Innovation in Contracting Strategy for a Master Services Agreement for Remediation of Low Level Radioactive Waste - 18381

The Port Hope Area Initiative (PHAI) is a federal environmental clean-up program. Its mandate is the remediation and local, long-term, safe management of approximately 1.7 million cubic metres of historic low-level radioactive waste in the adjacent communities of Port Hope and Port Granby in Southern Ontario, Canada. The PHAI is being undertaken by Canadian Nuclear Laboratories (CNL), on behalf of Atomic Energy of Canada Limited, a federal Crown corporation. It is currently one of the largest environmental remediation projects in Canada. The safety of workers, the public and the environment while delivering the PHAI on time and within budget is CNL's number one priority. The PHAI is being carried out as two projects - the Port Hope Project and the Port Granby Project. The Port Hope Project is the larger of the two and includes the cleanup of approximately 1.2 million cubic metres of historic waste from several locations, including the Port Hope Harbour, a closed municipal landfill and approximately 800 residential properties. This complex project requires contracting the services of qualified, skilled and experienced environmental remediation contractors to meet the diverse needs of the myriad tasks that comprise the remediation and restoration of all properties. This paper will highlight how the CNL contracting services team developed an innovative approach to a contracting strategy designed to deliver the safe execution of work and keep the project on time and within budget. The approach addresses the complexities of a scope of work that consists of multiple work packages to be executed both concurrently and in tandem, and that require highly specialized trades/skills, as well as high-level project management expertise to ensure seamless coordination among the various contractors. The author will discuss CNL's strategy to engage the market with a Request for Expression of Interest to identify potential qualified suppliers and gauge their level of interest, issue a Request for Prequalification (RFPQ) to determine eligible contractors and, ultimately, issue a Request for Proposal for a Master Services Agreement (MSA) that would competitively evaluate each contractor's direct experience, technical expertise, quality management programs, safety systems compliance and track record. Using CNL's experience as a case study, the paper will highlight how an innovative approach can positively affect project timelines by describing how CNL addressed the challenge associated with the limited time available to implement procurement processes and deliver a series of executed agreements while ensuring that work would begin on time and key project milestones would be met. The author will summarize how CNL's strategy put the project back on schedule, without compromising the process guideline/requirements, and ensured that a qualified and experienced set of contractors, committed to a strong safety culture, will be available to perform the work required when the cleanup in the Port Hope community begins in 2018. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Nuclear Data Uncertainty Quantification for Adjoint-Weighted Quantities via XGPT in Monte Carlo Codes

The Total Monte Carlo method (TMC) is an innovative approach to nuclear data uncertainty propagation. In TMC, a large number of independent ENDF files are randomly generated starting from nuclear models parameters and their uncertainties. These files are then processed with NJOY or similar codes to produce a set of formatted continuous-energy cross sections (i.e., ACE files), and independent Monte Carlo neutron transport simulations are run with these different ACE files as input. Finally the distributions of the considered response functions are obtained directly from the results of the Monte Carlo runs. Despite several improvements of the TMC method, this approach is often considered an inefficient way of propagating nuclear data uncertainties, as it requires several computationally expensive Monte Carlo runs. Covariance-based methods present important advantages for several applications, especially when different sources of uncertainties are to be investigated. For this reason, sensitivity analysis and uncertainty quantification capabilities are being implemented in several Monte Carlo neutron transport codes. On the other hand, the fact that no artificial multi-group covariance matrices are required and that higher moments of the responses distributions can be easily obtained, are definite advantages of the TMC method. In an effort to overcome the limitations of both approaches, a new method, called eXtended Generalized Perturbation Theory (XGPT) is under development. When performing nuclear data uncertainty propagation, such XGPT approach does not require generating discretized (i.e., multigroup) covariance matrices, and allows to estimate higher moments of the response probability distributions, via linear perturbation theory. One of the promising applications of the XGPT method involves its adoption in conjunction with the Proper Orthogonal Decomposition (POD) of nuclear data, to build a Reduced Order Model (ROM) for the approximation of thousands of independent TMC results in a single criticality source simulation. In the present work, this approach is employed for the first time to evaluate the impact of uncertainty in nuclear data on adjoint-weighted quantities. The method has been implemented in an extended version of the Serpent-2.1.24 Monte Carlo code and is demonstrated on two fast spectrum benchmarks, focusing on {sup 208}Pb nuclear data. A new method for propagating nuclear data uncertainties in criticality source Monte Carlo simulations has been developed. This eXtended Generalized Perturbation Theory (XGPT) approach allows to accurately reproduce reference Total Monte Carlo (TMC) uncertainty estimates in a single criticality source simulation. The present work aims to demonstrate that the proposed method can quantify nuclear data uncertainty based on adjoint-weighted quantities. The XGPT approach was applied to evaluate the impact of {sup 208}Pb nuclear data uncertainties on the effective prompt neutron lifetime (l{sub eff}) in two fast spectrum systems. The obtained XGPT results show a good agreement with the reference TMC results, obtained from independent Monte Carlo runs with {sup 208}Pb nuclear data from random TENDL-2013 evaluations. The XGPT method, implemented in a extended version of the Serpent Monte Carlo code and adopted along with the Proper Orthogonal Decomposition (POD) of the nuclear data, is able to provide an accurate reduced order model to approximate thousands TMC results within a single run, ensuring a large saving in computational requirements. The effect of {sup 208}Pb nuclear data uncertainties appears to be rather large. This is consistent with previous studies that adopted the same input random evaluations data from TENDL. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗
DOE OSTI2019

Upgrading Fast Pyrolysis Liquids

The liquid formed by the fast pyrolysis (FP) of biomass is commonly termed bio-oil. Biomass is converted to bio-oil through FP at 400-550°C typically at 1 atm. During FP, the biomass is held at temperature for a residence time on the order of 1-2 seconds. FP is beneficial from the standpoint that a large portion of the total mass and carbon contained in the biomass is converted and retained in the liquid bio-oil fraction. However, bio-oil is acidic, viscous, and thermally unstable. Bio-oil must be upgraded in order to be considered as a liquid transportation fuel or separated and further treated to produce value-added chemicals. Bio-oil is generally regarded as difficult to upgrade due to its thermal instability and chemical complexity which is derived in part from the incorporation of highly reactive species such as aldehydes and terminal olefins as well as the presence of sugars and anhydrosugar species which undergo secondary polymerization reactions when heated. Upgrading strategies considered in this chapter include methods to stabilize and deoxygenate bio-oil through low temperature hydroprocessing to stabilize bio-oil followed by higher temperature “deep hydrotreating” to remove the majority of oxygen present; converting bio-oil catalytically (often with zeolites such as HZSM-5) prior to condensation with catalysts inside the FP reactor or in a separate fixed or fluidized bed after the FP reactor; catalytic cracking with acid catalysts such as zeolites after condensation; or through physical or chemical separations to improve bio-oil stability, extract valuable chemicals, or produce H¬2. Bio-oil upgrading by co-processing with refinery streams such as vacuum gas oil in a fluid catalytic cracking (FCC) unit in a refinery has also been investigated. Numerous excellent reviews, perspectives and other chapters have been published in the preceding 7 years.[1-10] Reviews specific to individual sections within this chapter are at the beginning of the individual sections. This chapter is intended as an update to the original article authored by Prof. Anthony V. Bridgwater, Thermochemical Processing of Biomass: Conversion into Fuels, Chemicals and Power, First Edition, Edited by Robert C. Brown, © 2011 John Wiley & Sons, Ltd. We gratefully acknowledge the original contribution by Prof. Bridgwater and have kept much of his original discussions intact with updated references. The scope of this updated chapter includes references published since about 2010. In the interest of space many of the original references included in the original version were not included. Thus, Prof. Bridgwater’s original chapter should be viewed as a companion to this updated chapter to provide a holistic set of references to the numerous bio-oil upgrading processes discussed herein.

Albrecht, Karl O.↗
DOE OSTI2022

Estimating Drizzle Parameters by Aircraft Sampling

In-cloud supersaturation is calculated from aircraft derived measurements of the in-cloud vertical gradient of liquid water content, vertical velocity, the pt and 3 rd cloud droplet radius moments and a parameter related to the heat and mass transport during condensation and evaporation of cloud droplets. The aircraft data where taken during the VOCALS 2008 study in marine stratocumulus clouds off the coast of Chile. Approximately 16000 discrete samples, 2.5 meter in length, were used in the present analysis of in-cloud supersaturation and its variability, both of which are indicative of turbulent processes within the cloud and their significant impact on drizzle formation. Two additional drizzle parameters, the eddy persistence time and the variance of fluctuations in in-cloud droplet growth rate were also estimated from this data set. These results will help to constrain parameterizations of underlying turbulent microphysical processes of clouds and thereby advance the future development of warm cloud and precipitation models for climate simulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Polymer composites based on gypsum matrix

The role of polymers as retarder additives is to prolong the workability connected with setting time of gypsum. Various cellulose derivatives, soluble in water in concentration up to 1,5% by weight were applied taking different water/binder ratio. The hydration process of calcium sulfate hemihydrate (gypsum binder) into dihydrate (gypsum plaster) was observed by setting and calorimetric techniques. Scanning electron microscopy confirmed that the gypsum microstructure was varied when polymers are used. The mechanical properties of gypsum plasters were studied by bending strength test and they are correlated with sample microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The connected wedge theorem and its consequences

In the AdS/CFT correspondence, bulk causal structure has consequences for boundary entanglement. In quantum information science, causal structures can be replaced by distributed entanglement for the purposes of information processing. In this work, we deepen the understanding of both of these statements, and their relationship, with a number of new results. Centrally, we present and prove a new theorem, the n-to-n connected wedge theorem, which considers n input and n output locations at the boundary of an asymptotically AdS 2+1 spacetime described by AdS/CFT. When a sufficiently strong set of causal connections exists among these points in the bulk, a set of n associated regions in the boundary will have extensive-in-N mutual information across any bipartition of the regions. The proof holds in three bulk dimensions for classical spacetimes satisfying the null curvature condition and for semiclassical spacetimes satisfying standard conjectures. The n-to-n connected wedge theorem gives a precise example of how causal connections in a bulk state can emerge from large-N entanglement features of its boundary dual. It also has consequences for quantum information theory: it reveals one pattern of entanglement which is sufficient for information processing in a particular class of causal networks. We argue this pattern is also necessary, and give an AdS/CFT inspired protocol for information processing in this setting. Our theorem generalizes the 2-to-2 connected wedge theorem proven in [3]. We also correct some errors in the proof presented there, in particular a false claim that existing proof techniques work above three bulk dimensions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Screening green solvents for multilayer plastic film recycling processes

Multilayer (ML) plastic films are essential packaging materials that help protect products from diverse external factors; however, only 5% of all ML films are recycled in the United States. Solvent-based technologies are a promising alternative for recycling ML films because they enable recovery of constituent polymer resins. For example, the Solvent Targeted Recovery and Precipitation (STRAPTM) process sequentially dissolves and separates polymer components using a series of targeted solvent washes. A crucial design aspect of this process is the impact of selected solvents on human health and on the environment. Here, this work introduces a computational framework that integrates molecular modeling, process modeling, techno-economic analysis (TEA), and life-cycle analysis (LCA) to quickly screen green solvents for solvent-based ML recycling processes. Initial screening for solvents based on selectivity is performed by estimating temperature-dependent solubilities using molecular-scale models. Subsequent screening uses basic estimates of energy use and octanol-water partition coefficients (logP) as key measures of health, safety, and environmental hazards. Detailed process modeling, TEA, and LCA are used on a reduced set of promising solvents identified in early screening steps to more accurately determine how solvent selection and associated operating conditions impact overall economics and environmental impacts. The framework is used for the identification of green solvents (from a database of 1,000 solvents) that separate an industrial ML film composed of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET). Our analysis shows the effectiveness of the framework and reveals fundamental trade-offs between solvent greenness, solubility, and economics. Our work emphasizes the importance of taking a holistic systems view during solvent design and aims to inform the development of new processes for ML film recycling and the identification of new ML films that are easier to recycle.

economics↗
DOE OSTI2016

Achieving Actionable Results from Available Inputs: Metamodels Take Building Energy Simulations One Step Further

Modeling commercial building energy usage can be a difficult and time-consuming task. The increasing prevalence of optimization algorithms provides one path for reducing the time and difficulty. Many use cases remain, however, where information regarding whole-building energy usage is valuable, but the time and expertise required to run and post-process a large number of building energy simulations is intractable. A relatively underutilized option to accurately estimate building energy consumption in real time is to pre-compute large datasets of potential building energy models, and use the set of results to quickly and efficiently provide highly accurate data. This process is called metamodeling. In this paper, two case studies are presented demonstrating the successful applications of metamodeling using the open-source OpenStudio Analysis Framework. The first case study involves the U.S. Department of Energy's Asset Score Tool, specifically the Preview Asset Score Tool, which is designed to give nontechnical users a near-instantaneous estimated range of expected results based on building system-level inputs. The second case study involves estimating the potential demand response capabilities of retail buildings in Colorado. The metamodel developed in this second application not only allows for estimation of a single building's expected performance, but also can be combined with public data to estimate the aggregate DR potential across various geographic (county and state) scales. In both case studies, the unique advantages of pre-computation allow building energy models to take the place of topdown actuarial evaluations. This paper ends by exploring the benefits of using metamodels and then examines the cost-effectiveness of this approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗