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NASA NTRS1996

Task 7: ADPAC User's Manual

The overall objective of this study was to develop a 3-D numerical analysis for compressor casing treatment flowfields. The current version of the computer code resulting from this study is referred to as ADPAC (Advanced Ducted Propfan Analysis Codes-Version 7). This report is intended to serve as a computer program user's manual for the ADPAC code developed under Tasks 6 and 7 of the NASA Contract. The ADPAC program is based on a flexible multiple- block grid discretization scheme permitting coupled 2-D/3-D mesh block solutions with application to a wide variety of geometries. Aerodynamic calculations are based on a four-stage Runge-Kutta time-marching finite volume solution technique with added numerical dissipation. Steady flow predictions are accelerated by a multigrid procedure. An iterative implicit algorithm is available for rapid time-dependent flow calculations, and an advanced two equation turbulence model is incorporated to predict complex turbulent flows. The consolidated code generated during this study is capable of executing in either a serial or parallel computing mode from a single source code. Numerous examples are given in the form of test cases to demonstrate the utility of this approach for predicting the aerodynamics of modem turbomachinery configurations.

Hall, E. J.↗

DOE OSTI2014

Role of Genetic Polymorphisms in NFKB-Mediated Inflammatory Pathways in Response to Primary Chemoradiation Therapy for Rectal Cancer

Purpose: To investigate whether polymorphisms of genes related to inflammation are associated with pathologic response (primary endpoint) in patients with rectal cancer treated with primary chemoradiation therapy (PCRT). Methods and Materials: Genomic DNA of 159 patients with locally advanced rectal cancer treated with PCRT was genotyped for polymorphisms rs28362491 (NFKB1), rs1213266/rs5789 (PTGS1), rs5275 (PTGS2), and rs16944/rs1143627 (IL1B) using TaqMan single nucleotide polymorphism genotyping assays. The association between each genotype and pathologic response (poor response vs complete or partial response) was analyzed using logistic regression models. Results: The NFKB1 DEL/DEL genotype was associated with pathologic response (odds ratio [OR], 6.39; 95% confidence interval [CI], 0.78-52.65; P=.03) after PCRT. No statistically significant associations between other polymorphisms and response to PCRT were observed. Patients with the NFKB1 DEL/DEL genotype showed a trend for longer disease-free survival (log-rank test, P=.096) and overall survival (P=.049), which was not significant in a multivariate analysis that included pathologic response. Analysis for 6 polymorphisms showed that patients carrying the haplotype rs28362491-DEL/rs1143627-A/rs1213266-G/rs5789-C/rs5275-A/rs16944-G (13.7% of cases) had a higher response rate to PCRT (OR, 8.86; 95% CI, 1.21-64.98; P=.034) than the reference group (rs28362491-INS/rs1143627-A/rs1213266-G/rs5789-C/rs5275-A/rs16944-G). Clinically significant (grade ≥2) acute organ toxicity was also more frequent in patients with that same haplotype (OR, 4.12; 95% CI, 1.11-15.36; P=.037). Conclusions: Our results suggest that genetic variation in NFKB-related inflammatory pathways might influence sensitivity to primary chemoradiation for rectal cancer. If confirmed, an inflammation-related radiogenetic profile might be used to select patients with rectal cancer for preoperative combined-modality treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Modeling and simulation functional needs for molten salt reactor licensing

The modeling and simulation functional needs to license and design molten salt reactor concepts were assessed and an evaluation methodology was developed using a licensing-focused approach considering the modeling and simulation components that contribute to a molten salt reactor safety analysis report. These functional needs were prioritized by identifying the relationships between functional needs and using a quantitative weighting method to identify the most critical components to build a licensing case. This novel weighting method provided a list of functional needs prioritized relative to key advanced reactor licensing outcomes. In addition, functional need inputs were ranked to reveal those that feed the most modeling and simulation components. The findings from this prioritization effort were used to inform the modeling and simulation goals of the US Department of Energy Office of Nuclear Energy (DOE-NE) Molten Salt Reactor campaign.Modeling and simulation needs were grouped into three main categories: (1) source term definition, material accountancy, and radiological consequences, (2) safety analysis, and (3) steady-state neutronics and thermal hydraulics. Here, five near-term goals were identified among these focus areas that add value: (1) deploying a systems and safeguards analysis computational tool, (2) defining source terms for molten salt reactor analysis and interfacing with the US Nuclear Regulatory Commission on accident progression analysis, (3) developing point designs for liquid-fueled thermal-spectrum and fast-spectrum molten salt reactors, (4) building safety analysis specifications and reference solutions for Molten Salt Reactor Experiment transients, and (5) interfacing with the thermophysical and thermodynamic salt chemistry databases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Relaxed Bell inequalities with arbitrary measurement dependence for each observer

Bell's inequality was originally derived under the assumption that experimenters are free to select detector settings independently of any local “hidden variables” that might affect the outcomes of measurements on entangled particles. This assumption has come to be known as “measurement independence” (also referred to as “freedom of choice” or “settings independence”). For a two-setting, two-outcome Bell test, we derive modified Bell inequalities that relax measurement independence, for either or both observers, while remaining locally causal. We describe the loss of measurement independence for each observer using the parameters M 1 and M 2 , as defined by Hall in 2010, and also by a more complete description that adds two new parameters, which we call M 1 ^ and M 2 ^ , deriving a modified Bell inequality for each description. These “relaxed” inequalities subsume those considered in previous work as special cases, and quantify how much the assumption of measurement independence needs to be relaxed in order for a locally causal model to produce a given violation of the standard Bell-Clauser-Horne-Shimony-Holt (Bell-CHSH) inequality. We demonstrate that both relaxed Bell inequalities are tight bounds on the CHSH parameter by constructing locally causal models that saturate them. For any given Bell inequality violation, the new two-parameter and four-parameter models each require significantly less mutual information between the hidden variables and measurement settings than previous models. We conjecture that the new models, with optimal parameters, require the minimum possible mutual information for a given Bell violation. We also argue that, contrary to various claims in the literature, relaxing freedom of choice need not imply superdeterminism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2015

Basin-Scale Assessment of the Land Surface Energy Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

This paper compares the annual and monthly components of the simulated energy budget from the North American Land Data Assimilation System phase 2 (NLDAS-2) with reference products over the domains of the 12 River Forecast Centers (RFCs) of the continental United States (CONUS). The simulations are calculated from both operational and research versions of NLDAS-2. The reference radiation components are obtained from the National Aeronautics and Space Administration Surface Radiation Budget product. The reference sensible and latent heat fluxes are obtained from a multitree ensemble method applied to gridded FLUXNET data from the Max Planck Institute, Germany. As these references are obtained from different data sources, they cannot fully close the energy budget, although the range of closure error is less than 15%formean annual results. The analysis here demonstrates the usefulness of basin-scale surface energy budget analysis for evaluating model skill and deficiencies. The operational (i.e., Noah, Mosaic, and VIC) and research (i.e., Noah-I and VIC4.0.5) NLDAS-2 land surface models exhibit similarities and differences in depicting basin-averaged energy components. For example, the energy components of the five models have similar seasonal cycles, but with different magnitudes. Generally, Noah and VIC overestimate (underestimate) sensible (latent) heat flux over several RFCs of the eastern CONUS. In contrast, Mosaic underestimates (overestimates) sensible (latent) heat flux over almost all 12 RFCs. The research Noah-I and VIC4.0.5 versions show moderate-to-large improvements (basin and model dependent) relative to their operational versions, which indicates likely pathways for future improvements in the operational NLDAS-2 system.

Energy↗

NASA NTRS2017

The Use of Sun Elevation Angle for Stereogrammetric Boreal Forest Height in Open Canopies

Stereogrammetry applied to globally available high resolution spaceborne imagery (HRSI; less than 5 m spatial resolution) yields fine-scaled digital surface models (DSMs) of elevation. These DSMs may represent elevations that range from the ground to the vegetation canopy surface, are produced from stereoscopic image pairs (stereo pairs) that have a variety of acquisition characteristics, and have been coupled with lidar data of forest structure and ground surface elevation to examine forest height. This work explores surface elevations from HRSI DSMs derived from two types of acquisitions in open canopy forests. We (1) apply an automated mass-production stereogrammetry workflow to along-track HRSI stereo pairs, (2) identify multiple spatially coincident DSMs whose stereo pairs were acquired under different solar geometry, (3) vertically co-register these DSMs using coincident spaceborne lidar footprints (from ICESat-GLAS) as reference, and(4) examine differences in surface elevations between the reference lidar and the co-registered HRSI DSMs associated with two general types of acquisitions (DSM types) from different sun elevation angles. We find that these DSM types, distinguished by sun elevation angle at the time of stereo pair acquisition, are associated with different surface elevations estimated from automated stereogrammetry in open canopy forests. For DSM values with corresponding reference ground surface elevation from spaceborne lidar footprints in open canopy northern Siberian Larix forests with slopes less than10, our results show that HRSI DSM acquired with sun elevation angles greater than 35deg and less than 25deg (during snow-free conditions) produced characteristic and consistently distinct distributions of elevation differences from reference lidar. The former include DSMs of near-ground surfaces with root mean square errors less than 0.68 m relative to lidar. The latter, particularly those with angles less than 10deg, show distributions with larger differences from lidar that are associated with open canopy forests whose vegetation surface elevations are captured. Terrain aspect did not have a strong effect on the distribution of vegetation surfaces. Using the two DSM types together, the distribution of DSM-differenced heights in forests (6.0 m, sigma = 1.4 m) was consistent with the distribution of plot-level mean tree heights (6.5m, sigma = 1.2 m). We conclude that the variation in sun elevation angle at time of stereo pair acquisition can create illumination conditions conducive for capturing elevations of surfaces either near the ground or associated with vegetation canopy. Knowledge of HRSI acquisition solar geometry and snow cover can be used to understand and combine stereogrammetric surface elevation estimates to co-register rand difference overlapping DSMs, providing a means to map forest height at fine scales, resolving the vertical structure of groups of trees from spaceborne platforms in open canopy forests.

Paul M Montesano↗

DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. In this paper, how we have developed one of the HUNTER modules, the individual module for evaluating performance shaping factors (PSFs), is introduced. The PSF refers to any factor that influences human performance such as workload or complexity. It has been used for highlighting human errors and adjusting the error probabilities in the existing HRA. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, which is the representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also design the individual module composed of the two functions: 1) the PSF qualification function that automatically or manually evaluates a PSF level, and 2) the PSF quantification function that dynamically or statically determines the PSF multiplier values and integrate them to adjust human error probabilities (HEPs). How each function works with the SPAR-H PSFs and how the PSFs adjust the HEPs are investigated through literature and discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2018

A predictive 0-D HCCI combustion model for ethanol, natural gas, gasoline, and primary reference fuel blends

Homogeneous Charge Compression Ignition (HCCI) is a promising advanced combustion concept with high thermal efficiency and low exhaust emissions. This work purposes a computationally-efficient, zero-dimensional (0-D) HCCI combustion model that does not need to solve any differential equations. To develop the burn rate correlations, experimental HCCI data of ethanol, natural gas, E10-gasoline, and Primary Reference Fuel (PRF) blends was collected on a CFR engine. The burn rate model is built based on the individual cycle mass fraction burned (MFB) curves calculated from the experimental data. CA0 can be predicted from an ignition delay correlation. Once CA0 is known, CA50 and CA90 can be predicted based on CA0 and the charge-mass equivalence ratio Φ'. Then, with CA0, 50 and 90 known, a Wiebe function can be constructed to represent the MFB curve and burn rate. For PRF blends, low-temperature and high-temperature heat releases (LTHR and HTHR) are modeled by two Wiebe functions with Φ' and PRF number dependence. The fitted model has high accuracy compared to the experimental data with R 2 values generally greater than 0.97. Finally, various ignition delay correlations from the literature are also tested against the experimentally collected data and some modifications to the correlations are suggested.

42 ENGINEERING↗

DOE OSTI2024

Via Machinae 2.0 : Full-sky, model-agnostic search for stellar streams in Gaia DR2

ABSTRACT We present an update to Via Machinae, an automated stellar stream-finding algorithm based on the deep learning anomaly detector ANODE. Via Machinae identifies stellar streams within Gaia, using only angular positions, proper motions, and photometry, without reference to a model of the Milky Way potential for orbit integration or stellar distances. This new version, Via Machinae 2.0, includes many improvements and refinements to nearly every step of the algorithm, that altogether result in more robust and visually distinct stream candidates than our original formulation. In this work, we also provide a quantitative estimate of the false positive rate of Via Machinae 2.0 by applying it to a simulated Gaia-mock catalogue based on galaxia, a smooth model of the Milky Way that does not contain substructure or stellar streams. Finally, we perform the first full-sky search for stellar streams with Via Machinae 2.0, identifying 102 streams at high significance within the Gaia Data Release 2, of which only 10 have been previously identified. While follow-up observations for further confirmation are required, taking into account the false positive rate presented in this work, we expect approximately 90 of these stream candidates to correspond to real stellar structures.

Astronomy & Astrophysics↗

DOE OSTI2015

Chemical Looping Gasification for Hydrogen Enhanced Syngas Production with In-Situ CO 2 Capture

This document is the final report for the project titled “Chemical Looping Gasification for Hydrogen Enhanced Syngas Production with In-Situ CO 2 Capture” under award number FE0012136 for the performance period 10/01/2013 to 12/31/2014.This project investigates the novel Ohio State chemical looping gasification technology for high efficiency, cost efficiency coal gasification for IGCC and methanol production application. The project developed an optimized oxygen carrier composition, demonstrated the feasibility of the concept and completed cold-flow model studies. WorleyParsons completed a techno-economic analysis which showed that for a coal only feed with carbon capture, the OSU CLG technology reduced the methanol required selling price by 21%, lowered the capital costs by 28%, increased coal consumption efficiency by 14%. Further, using the Ohio State Chemical Looping Gasification technology resulted in a methanol required selling price which was lower than the reference non-capture case.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

NASA NTRS1980

Ignition of lean fuel-air mixtures in a premixing-prevaporizing duct at temperatures up to 1000 K

Conditions were determined in a premixing prevaporizing fuel preparation duct at which ignition occurred. An air blast type fuel injector with nineteen fuel injection points was used to provide a uniform spatial fuel air mixture. The range of inlet conditions where ignition occurred were: inlet air temperatures of 600 to 1000 K air pressures of 180 to 660 kPa, equivalence ratios (fuel air ratio divided by stoichiometric fuel air ratio) from 0.12 to 1.05, and velocities from 3.5 to 30 m/s. The duct was insulated and the diameter was 12 cm. Mixing lengths were varied from 16.5 to 47.6 and residence times ranged from 4.6 to 107 ms. The fuel was no. 2 diesel. Results show a strong effect of equivalence ratio, pressure and temperature on the conditions where ignition occurred. The data did not fit the most commonly used model of auto-ignition. A correlation of the conditions where ignition would occur which apply to this test apparatus over the conditions tested is (p/V) phi to the 1.3 power = 0.62 e to the 2804/T power where p is the pressure in kPa, V is the velocity in m/e, phi is the equivalence ratio, and T is the temperature in K. The data scatter was considerable, varying by a maximum value of 5 at a given temperature and equivalence ratio. There was wide spread in the autoignition data contained in the references.

Tacina, R. R.↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗

NASA NTRS2021

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Circumboreal forests are currently experiencing rapid climate warming which is altering their structure, productivity, and status as a carbon sink. Very-high resolution (VHR, <2 m) stereo derived digital surface models are available to monitor these forests, but, a similar resolution digital terrain model (DTM) is required to extract information about tree height, which is often used to estimate carbon content. To our knowledge, no openly available VHR DTM currently exists. To address this need, we developed approaches to extract DTMs by filtering VHR stereo point clouds (PCs) in sparse canopies of Alaska. Our evaluation consisted of two stereo processing methods with three PC search radii, at six different tree canopy cover (TCC) intervals. We found VHR DTMs were robust for estimating bare ground at TCC intervals less than 40% with vertical errors <1.6 m using airborne small footprint light detection and ranging (LiDAR) as reference.

Christopher S R Neigh↗

NASA NTRS2021

Estimating Bare Earth in Sparse Boreal Forests With WorldView Stereo Imagery

Christopher S. R. Neigh↗

DOE OSTI2013

On the use of genetic algorithm to optimize industrial assets lifecycle management under safety and budget constraints

The purpose of this paper is to describe the method and tool dedicated to optimize investments planning for industrial assets. These investments may either be preventive maintenance tasks, asset enhancements or logistic investments such as spare parts purchases. The two methodological points to investigate in such an issue are: 1. The measure of the profitability of a portfolio of investments 2. The selection and planning of an optimal set of investments 3. The measure of the risk of a portfolio of investments The measure of the profitability of a set of investments in the IPOP tool is synthesised in the Net Present Value indicator. The NPV is the sum of the differences of discounted cash flows (direct costs, forced outages...) between the situations with and without a given investment. These cash flows are calculated through a pseudo-Markov reliability model representing independently the components of the industrial asset and the spare parts inventories. The component model has been widely discussed over the years but the spare part model is a new one based on some approximations that will be discussed. This model, referred as the NPV function, takes for input an investments portfolio and gives its NPV. The second issue is to optimize the NPV. If all investments were independent, this optimization would be an easy calculation, unfortunately there are two sources of dependency. The first one is introduced by the spare part model, as if components are indeed independent in their reliability model, the fact that several components use the same inventory induces a dependency. The second dependency comes from economic, technical or logistic constraints, such as a global maintenance budget limit or a safety requirement limiting the residual risk of failure of a component or group of component, making the aggregation of individual optimum not necessary feasible. The algorithm used to solve such a difficult optimization problem is a genetic algorithm. After a description of the features of the software a test case is presented showing the influence of the optimization algorithm parameters on its efficiency to find an optimal investments planning. (authors)

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Decoupling relationship between economic output and carbon emission in the Chinese construction industry

By positioning in the discourse that economic output is always coupled with natural resource depletion, pollution, and carbon emission, decoupling analysis is widely adopted to evaluate how “quality” economic growth can lead to fewer such downsides so as to encourage sustainable development. This paper aims at examining the decoupling relationship between economic output and carbon emission by focusing on China's construction industry, which is a pillar industry for national economic growth, meanwhile contributes a huge amount of carbon emission. The method of Tapio decoupling model is used to examine the decoupling relationships at both national and provincial levels from 2005 to 2015. It continues to identify the driving force leading to a certain decoupling state by adopting the logarithmic mean Divisia index (LMDI). Results show that: (1) there existed an expansive decoupling relationship between economic growth and construction carbon emission in most provinces of China during 2005–2015; (2) Shanghai presented the best decoupling performance, while in contrast, other provinces such as Guizhou and Fujian displayed expansive negative decoupling state; and (3) “Economic output” played the most significant role in inhibiting the decoupling at both national and provincial levels, while “Indirect carbon intensity” was the main driver for promoting the national decoupling. Although the paper refers to the specific construction of China, the decoupling analysis approach can be extended to other countries as well as to other pollutants such as land pollution, waste water and haze. The understanding of driving forces for the decoupling state in China's construction industry provides international policy-makers with valuable reference for formulating effective measures to balance the dilemma between economic output and carbon emission.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Conformational Complexity in the LH2 Antenna of the Purple Sulfur Bacterium Allochromatium vinosum Revealed by Hole-Burning Spectroscopy

This work discusses the protein conformational complexity of the B800–850 LH2 complexes from the purple sulfur bacterium Allochromatium vinosum, focusing on the spectral characteristics of the B850 chromophores. Low-temperature B850 absorption and the split B800 band shift blue and red, respectively, at elevated temperatures, revealing isosbestic points. The latter indicates the presence of two (unresolved) conformations of B850 bacteriochlorophylls (BChls), referred to as conformations 1 and 2, and two conformations of B800 BChls, denoted as B800R and B800B. The energy differences between average site energies of conformations 1 and 2, and B800R and B800B are similar (~200 cm –1 ), suggesting weak and strong hydrogen bonds linking two major subpopulations of BChls and the protein scaffolding. Although conformations 1 and 2 of the B850 chromophores, and B800R and B800B, exist in the ground state, selective excitation leads to 1 → 2 and B800R → B800B phototransformations. Different static inhomogeneous broadening is revealed for the lowest energy exciton states of B850 (fwhm ~195 cm –1 ) and B800R (fwhm ~140 cm –1 ). To describe the 5 K absorption spectrum and the above-mentioned conformations, we employ an exciton model with dichotomous protein conformation disorder. We show that both experimental data and the modeling study support a two-site model with strongly and weakly hydrogen-bonded B850 and B800 BChls, which under illumination undergo conformational changes, most likely caused by proton dynamics.

59 BASIC BIOLOGICAL SCIENCES↗