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At least 991 records · Page 55

Unleashed from constrained optimization: quantum computing for quantum chemistry employing generator coordinate inspired method

Hybrid quantum-classical approaches offer potential solutions to quantum chemistry problems, yet they often manifest as constrained optimization problems. Here, we explore the interconnection between constrained optimization and generalized eigenvalue problems through the Unitary Coupled Cluster (UCC) excitation generators. Inspired by the generator coordinate method, we employ these UCC excitation generators to construct non-orthogonal, overcomplete many-body bases, projecting the system Hamiltonian into an effective Hamiltonian, which bypasses issues such as barren plateaus that heuristic numerical minimizers often encountered in standard variational quantum eigensolver (VQE). Diverging from conventional quantum subspace expansion methods, we introduce an adaptive scheme that robustly constructs the many-body basis sets from a pool of the UCC excitation generators. This scheme supports the development of a hierarchical ADAPT quantum-classical strategy, enabling a balanced interplay between subspace expansion and ansatz optimization to address complex, strongly correlated quantum chemical systems cost-effectively, setting the stage for more advanced quantum simulations in chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing Microstructure-induced Swelling & Thermal Property Changes in Ion-Irradiated Oxide Fuels using Laser-generated Surface Acoustic Waves

Radiation of fuel rods with neutrons during a fission reaction in a nuclear reactor is known to affect the material microstructure of the fuel as a result of fission fragment damage, and lead to the formation of atomic-level defects such as voids, dislocation loops, and lattice swelling from fission-gas release. A consequence of the radiation-induced damage in nuclear fuels is the drastic alteration of material properties, in particular, the reduction of the thermal conductivity – a key parameter that governs the transport of thermal energy released from fissile fuel atoms to the surrounding coolant. Swelling can induce high stresses and ultimate failure of the cladding. A fundamental understanding of the role of radiation-induced damage on the thermal transport and mechanical properties of nuclear fuels is therefore critical for efficient, reliable and safe operation of a nuclear power plant. As opposed to conventional post-irradiation examination techniques that are often time-consuming and require significant sample preparation, laser-based characterization methods have emerged as promising non-contact, non-destructive tools to measure the evolution of microstructure-induced material property changes. Moreover, laser methods offer the promise of in-situ characterization while the material is being irradiated. This project aims to develop an improved understanding of the impact of radiation-induced changes to material microstructure on the thermal and elastic properties of nuclear materials. A laser ultrasonic technique, known as the transient grating (TG) spectroscopy method, is used to simultaneously measure thermal diffusivity and elastic properties in unirradiated and ion-irradiated oxide nuclear fuel samples. The results will complement on-going investigations on electron- and phonon-mediated thermal transport in nuclear materials and will provide foundational work for incorporating the influence of defects in fuel performance codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Technology Case Study: Techno-Economic and Life Cycle Analysis for Microalgae Conversion Pathways to Fuels and Products

This technology case study report details the cost and sustainability prospects for an emerging feedstock - microalgae - converted to fuels and products via a fractionation and upgrading approach termed combined algae processing (CAP). Detailed techno-economic analysis (TEA) and life cycle analysis (LCA) are conducted for the conversion of farmed algae biomass, with two primary scenarios considering the conversion of either high-compositional-quality biomass enriched in lipids (high-lipid [HL]) or lower-quality biomass enriched in protein (high-protein [HP]). Each scenario employs a different biorefinery configuration tailored towards extracting the maximum value from the given biomass composition. The HL scenario produces fuels and non-isocyanate polyurethane (NIPU) as the primary products, while the HP scenario products fuels and a residual solid coproduct which can be used as a co-feed for producing thermoplastics. The results for the HL scenario were particularly promising, with a minimum fuel selling price (MFSP) of $\$$3.68 per gasoline gallon equivalent (GGE) and fuel GHG emissions translating to 54%-76% reduction compared to petroleum fuels depending on the coproduct handling method used. In contrast, the HP scenario faced more challenges in producing biofuels economically, projecting an MFSP of $\$$7.92/GGE despite significant revenues from the residual algae solids. LCA results for the HP case reflected a 24% reduction potential in biorefinery-level GHG emissions. However, these GHG reductions were primarily associated with the thermoplastic coproduct, which accounted for 93% of all biorefinery outputs by mass. Using a process-level allocation method, carbon intensity results were less promising, indicating a net increase in fuel GHG emissions versus petroleum fuels and highlighting the reliance of this scenario on the thermoplastic coproduct.

09 BIOMASS FUELS↗

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Healthcare Needs of the State: Quantitative Analysis

Prior to the COVID-19 pandemic, US hospitals relied on static projections of future trends for long-term planning and were only beginning to consider forecasting methods for short-term planning of staffing and other resources. With the overwhelming burden imposed by COVID-19 on the health care system, an emergent need exists to accurately forecast hospitalization needs within an actionable timeframe. Our goal was to leverage an existing COVID-19 case and death forecasting tool to generate the expected number of concurrent hospitalizations, occupied intensive care unit (ICU) beds, and in-use ventilators 1 day to 4 weeks in the future for New Mexico and each of its five health regions. We developed a probabilistic model that took as input the number of new COVID-19 cases for New Mexico from Los Alamos National Laboratory’s COVID-19 Forecasts Using Fast Evaluations and Estimation tool, and we used the model to estimate the number of new daily hospital admissions 4 weeks into the future based on current statewide hospitalization rates. The model estimated the number of new admissions that would require an ICU bed or use of a ventilator and then projected the individual lengths of hospital stays based on the resource need. By tracking the lengths of stay through time, we captured the projected simultaneous need for inpatient beds, ICU beds, and ventilators. We used a postprocessing method to adjust the forecasts based on the differences between prior forecasts and the subsequent observed data. Thus, we ensured that our forecasts could reflect a dynamically changing situation on the ground. Forecasts made between September 1 and December 9, 2020, showed variable accuracy across time, health care resource needs, and forecast horizon. Forecasts made in October, when new COVID-19 cases were steadily increasing, had an average accuracy error of 20.0%, while the error in forecasts made in September, a month with low COVID-19 activity, was 39.7%. Across health care use categories, state-level forecasts were more accurate than those at the regional level. Although the accuracy declined as the forecast was projected further into the future, the stated uncertainty of the prediction improved. Forecasts were within 5% of their stated uncertainty at the 50% and 90% prediction intervals at the 3- to 4-week forecast horizon for state-level inpatient and ICU needs. However, uncertainty intervals were too narrow for forecasts of state-level ventilator need and all regional health care resource needs. Real-time forecasting of the burden imposed by a spreading infectious disease is a crucial component of decision support during a public health emergency. Our proposed methodology demonstrated utility in providing near-term forecasts, particularly at the state level. This tool can aid other stakeholders as they face COVID-19 population impacts now and in the future.

60 APPLIED LIFE SCIENCES↗

Rolling Behavior of Surface Tagged Aluminum 6061 using Photoluminescent Oxides

Physical tagging of nuclear fuel is potentially one way of tracking throughout the fuel lifecycle. The process of tagging can take many forms, but one promising method is to embed a small amount of photoluminescent particles in the surface of a material which are not detectable under normal illumination but are readily visible under excitation by ultraviolet light. The goal of this project was to explore the potential to tag simulated nuclear fuel cladding with small ceramic particles, via laser beam welding or gas tungsten arc welding, and measure the photoluminescent response. Surface tagging using this method has demonstrated viability and detectability throughout this project; work in FY24 focused on the survivability of these tags through subsequent deformation processing similar to what taggants in a fuel manufacturing environment would be subjected to. This work demonstrated that particles are readily visible in the as-welded state (i.e., before subsequent rolling treatment to represent mechanical processing of a fuel material), but visibility is reduced as the deformation is induced. Despite the reduction in photoluminescence, the taggants are still visible after rolling processes are performed, making this surface tagging technique a promising candidate for nuclear fuel cladding tagging. This work demonstrated, though, that targeted optimization work would be necessary to develop a robust taggant depending on the fidelity and luminescent properties required.

36 MATERIALS SCIENCE↗

A Project Lifetime Approach to the Management of Induced Seismicity Risk at Geologic Carbon Storage Sites

The geologic storage of carbon dioxide (CO 2 ) is one method that can help reduce atmospheric CO 2 by sequestering it into the subsurface. Large-scale deployment of geologic carbon storage, however, may be accompanied by induced seismicity. We present a project lifetime approach to address the induced seismicity risk at these geologic storage sites. This approach encompasses both technical and nontechnical stakeholder issues related to induced seismicity and spans the time period from the initial consideration phase to postclosure. These recommendations are envisioned to serve as general guidelines, setting expectations for operators, regulators, and the public. They contain a set of seven actionable focus areas, the purpose of which are to deal proactively with induced seismicity issues. Although each geologic carbon storage site will be unique and will require a custom approach, these general best practice recommendations can be used as a starting point to any site-specific plan for how to systematically evaluate, communicate about, and mitigate induced seismicity at a particular reservoir.

58 GEOSCIENCES↗

VTO FY20Q4 quarterly report

Project Objective.This project has three objectives: (1) tuning microstructures of 3D-printed SSE separators,(2) determining material and processing compatibilities with cathode printing,and (3)3D printing of sintering-free SSE separators.Project Impact.All-solid-state lithium batteries are difficult to process due to the brittleness of ceramic materials, poor solid-solid contact, and electrolyte-electrode stability issues. As a result, the energy and power density and also cycling stability are far from satisfying. This project will address fabrication difficulties by using state-of-the-art 3D-printing techniques that can introduce 3D interfaces and architectures to enhance solid-solid contact and reduce charge transfer resistance. Success will benefit the DOE by establishing the best manufacturing methods for ASSBsto achieve VTO goals on the performance of beyond Li-ion batteries. Approach.The project employs 3D-printing techniques to manufacture SSEs and related components for ASSBs. The team starts with direct ink writing (DIW) to develop ink recipes with desired rheological properties and explore post-sintering approaches to achieve high densification. In parallel with DIW3D printing, the team also explores other 3D printing options, such as projection microstereolithography (PuSL). Both sintering and sintering-free approaches can gain benefit from 3D printing and therefore will be investigated.Out-Year Goals.The team will determine particle sizes and morphologies as well as post-processing conditions that deliver good ionic conductivity and charge transfer properties of LLZTO separators. They will examine co-sintering of LLZTO/cathode and determine the effects of material, particle size, surface coating, and sintering conditions.Collaborations.Microstructures, ionic conductivities, and mechanical properties will be provided to the LLNL simulation team, led by PI B. Wood, for establishing and validating phase-field modeling methods.

36 MATERIALS SCIENCE↗

Decommissioning of the V1 Nuclear Power Plant Jaslovske Bohunice - 20270

The paper focuses on introducing the approach and method applied for decommissioning of the V1 nuclear power plant (further the 'V1 NPP') located in Jaslovske Bohunice in the Slovak Republic, to the conference participants. The Paper outlines activities and steps necessary to comply with the requirements contained in the decision of the Slovak government from 1999 regarding the early shutdown of the V1 NPP. The company responsible for the V1 NPP decommissioning is Jadrova a vyradovacia spolocnost, a.s., (further JAVYS) with the State as a sole shareholder. On the basis of the V1 NPP Decommissioning Conceptual Plan, out of four assessed options, JAVYS selected the immediate decommissioning option (the 'IDO') for the V1 NPP. On the basis of multi-criteria analysis, the IDO specified the approach of immediate and continuous dismantling of equipment followed by demolition of buildings and preparation of the site for its further potential use. The IDO also included the summary of technical, environmental, legislative information as well as the determination of assumed costs for decommissioning of the V1 NPP. Prior to commencement of the V1 NPP decommissioning, within the process of termination of operation, activities connected with de-fuelling, monitoring, processing of historical waste and, not to forget, the process of obtaining the license for the V1 NPP decommissioning were executed. JAVYS decided to divide the decommissioning process into two stages. In 2011, JAVYS obtained a license for the first stage of the V1 NPP decommissioning. Within this stage, dismantling of inactive equipment, demolitions of inactive buildings, monitoring of systems and preparatory works for the upcoming stage of decommissioning were implemented. In 2015, in line with the license for the 2. stage of the V1 NPP decommissioning, the activities of decontamination and dismantling of contaminated and active equipment as well as demolitions of remaining buildings began. In this stage radioactive waste (RAW) produced during the decommissioning is to be processed. After decontamination, the material fulfilling the free release criteria is to be released into the environment, the site is to be cleared from the scope of the Atomic Act and released from the surveillance of the national regulators. Future application of certain methods and techniques for decontamination and dismantling in similar environments might bring an added value to the operators. Paper includes a description of best practices for Nuclear Power Plant VVER type reactors decommissioning. Schedule comparison is given to show how the critical path of certain projects is being managed. Application of the International Standard for Decommissioning Costing (ISDC) methodology provides a uniform method which enables comparison of cost estimates to other nuclear facilities under decommissioning. The cost estimate for the V1 NPP decommissioning has been continuously updated based on more advanced and detailed information on the decommissioning activities and projects. Monitoring of progress of the V1 NPP decommissioning is performed via four key-performance indicators. The Earned Value Management (EVM) methodology is used for evaluating time and cost aspect of decommissioning activities while waste conditioning index is calculated by comparing the actually produced waste to planned values of waste for a respective monitored period. Radiological safety index is assessed by comparison of the personnel records on the individual yearly doses received by each respective employee to the boundary value. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Low-Environmental-Impact Monitoring of CO 2 Using Seismic Methods in North Dakota

Conference poster presented at American Association of Petroleum Geologists (AAPG) Carbon Capture, Utilization, and Storage (CCUS) Conference, Houston, Texas, March 28–30, 2022. In 2021, the Energy & Environmental Research Center initiated a multiyear research project associated with Red Trail Energy’s Carbon Capture and Storage Project. The research is based on the scalable automated sparse seismic array (SASSA), a lower-cost, less invasive seismic method that could replace the large-scale 3D seismic surveys by using four stationary seismic sources called surface orbital vibrators (SOVs) and a small number of seismic sensors deployed sparsely within the same 8-square-mile area investigated with a 3D seismic survey conducted in 2019.

01 COAL, LIGNITE, AND PEAT↗

Risk Model for EM Decision Support Toolsets

The Government Office of Accountability (GAO) has published several reports identifying the need for the Department of Energy (DOE) Office of Environmental Management (EM) to address mounting costs for DoE's cleanup program. DOEEM could greatly benefit from independent decision tool-sets/models that would allow them to evaluate options and inform business decision at the enterprise level considering site-specific life cycle costs and system plans. Program goals: Develop a tool-set that enables EM to independently evaluate alternatives, assess outcomes from different contracting strategies, and inform critical decisions for the enterprise. Project goals: Adaption of a Risk Model for integration with complimentary tool-sets for project level decision making. Operational Events: Discrete event model that evaluates operational variables (e.g. capacity, throughput, maintenance constraints) and identify bottlenecks. Identifying and Bounding Project Risk: Identify risks that impact confidence in meeting goals (e.g. production). Life cycle Cost: Evaluate impacts of staffing levels, inventory, and capital investments on life cycle costs. Methods and approach: Monte Carlo Analysis is being executed to generate results: Input derives from Risk Register Data; Tied to Projected and Target Schedules; Incorporates float duration within the model. Assumes associated risk mitigation actions being completed within a timeline of five fiscal years. Metrics include: Confidence in Meeting Production Goal; Confidence in Safety Standards; Confidence in Continuous Operation; Other Metrics can be added as appropriate regarding specific site needs. The adapted risk model can be used as a stand alone decision tool or can be integrated complementary tool-sets (i.e. process and cost models) for project-specific decisions. These support tool-sets can then be integrated with others for site- and complex- level evaluations. Future work includes designing an adaptable and modular framework that would allow integration of multiple tool-sets for holistic and/or targeted evaluation of alternative strategies for decision making that could lead to risk and cost reduction across the enterprise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Large-Scale, GPU-Enhanced DFTB Approaches for Probing Multi-Component Alloys

The major goals of the project are to develop and apply GPU-enhanced density functional theory tight binding (DFTB) calculations for efficient simulations of structural materials of alloy systems. The figure below depicts the GPU algorithmic developments on the left that will be carried out, and the solid-state structures on the right are representative of the complex alloys that can be computed with the GPU-enhanced DFTB approach. The methodology and tools developed in this project encompass accurate intermolecular potentials and GPU enhancements to the density functional tight binding (DFTB) approach for high-throughput ab initio molecular dynamics calculations of multi-component alloys at elevated temperatures. While classical molecular dynamics can handle hundreds of thousands of atoms, it cannot provide a first-principles based description of large, multi-component alloys at the predictive quantum level. At the other extreme, conventional Kohn-Sham DFT methods can probe the true quantum nature of chemical systems; however, these methods cannot tackle the large sizes relevant to these multi-component systems. The DFTB-based ab initio molecular dynamics approach (coupled with our in-house GPU capabilities for enhanced speed) used in this project provides a viable approach for probing these large systems at a quantum level of detail that is significantly faster than current first-principle methods Collectively, the capabilities developed in this project directly respond to DOE HBCU-OMI, AOI 2-1 initiatives by (1) enabling accurate and efficient predictions and (2) bringing a fundamental understanding of structural interactions in these complex systems at elevated temperatures.

20 FOSSIL-FUELED POWER PLANTS↗

Sitka Energy Inventory

The City and Borough of Sitka was chosen for an Energy Technology Innovation Partner Project award starting in Fall 2023, the third cohort of the program. The scope of the following work was driven by the city, as well as the city-appointed Sustainability Commission. The community asked for a method to track their reliance on outside fuel sources, as well as the emissions associated with those fuels and other processes in Sitka. The Pacific Northwest National Laboratory (PNNL) provided research and methodology in line with this community driven ask. This project is a community wide inventory, requiring methods to estimate the fuel usage and emissions from various industries. For each estimate, PNNL presents methodologies that can be repeated by the community in future years to understand how the city is changing.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DESI mock challenge: Halo and galaxy catalogues with the bias assignment method

We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. We aim to produce mock galaxy catalogues capable of generating accurate covariance matrices for a number of cosmological probes that are expected to be measured in current and forthcoming galaxy redshift surveys (e.g. two- and three-point statistics). The construction of the catalogues shown in this paper is part of a mock-comparison project within the Dark Energy Spectroscopic Instrument (DESI) collaboration. We use the bias assignment method ( BAM ) to model the statistics of halo distribution through a learning algorithm using a few detailed N-body simulations, and approximated gravity solvers based on Lagrangian perturbation theory. We introduce cosmic-web-dependent corrections to modelling redshift-space distortions at the N-body level – both in the halo and galaxy distributions –, as well as a multi-scale approach for accurate assignment of halo properties. Using specific models of halo occupation distributions to populate halos, we generate galaxy mocks with the expected number density and central-satellite fraction of emission-line galaxies, which are a key target of the DESI experiment. BAM generates mock catalogues with per cent accuracy in a number of summary statistics, such as the abundance, the two- and three-point statistics of halo distributions, both in real and redshift space. In particular, the mock galaxy catalogues display ~3%-10% accuracy in the multipoles of the power spectrum up to scales of k ~ 0.4 h -1 Mpc. We show that covariance matrices of two- and three-point statistics obtained with BAM display a similar structure to the reference simulation. BAM offers an efficient way to produce mock halo catalogues with accurate two- and three-point statistics and is able to generate a variety of multi-tracer catalogues with precise covariance matrices of several cosmological probes. We discuss future developments of the algorithm towards mock production in DESI and other galaxy-redshift surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of Time-Series Gap-Filling Methods for Solar Irradiance Applications

A complete solar resource data set is essential for any stage of a solar energy project - from feasibility studies to daily operations. But measured or modeled solar resource data are prone to data gaps and data quality issues. To mitigate these issues, a data imputation process should be implemented to obtain a complete and reliable temporal and spatial data series. This study focused on imputing temporal scales by applying random and artificial data gaps and then implementing eight imputation methods, including the Kalman filtering and smoothing and stine interpolations. These methods were implemented on 1-minute to half hourly irradiance data for 1 year using a few locations from the National Solar Radiation Database (NSRDB) and ground measurement data set. The results demonstrated that some of the simpler methods, such as the stine and linear interpolation methods, were the relatively best models based on the statistical metrics for imputing NSRDB and ground measurement data, respectively.

14 SOLAR ENERGY↗

Sample Preparation Laboratory (SPL) Best Practices: CGD as the Primary Acceptance Method

The traditional paradigm applied to the construction of nuclear safety related systems, structures, and components (SSCs), like SPL, involves an owner/licensee hiring an EPC firm with an NQA 1 program to manage the engineering, procurement, and construction of the desired SSC. This traditional approach would have posed significant barriers to the successful completion of the SPL. As a smaller capital project, in the $\$$100–$\$$200 million range, there was concern that employing one of the larger EPC companies would escalate costs and extend the projected schedule beyond what would be feasible for the Department of Energy (DOE). The traditional acceptance method employed for nuclear facilities with credited safety functions requires the use of an EPC firm applying American Society of Mechanical Engineers (ASME) NQA 1 nuclear quality assurance (NQA) to accept safety SSCs. In lieu of this approach, INL elected to apply its own NQA 1 program to hire an EPC firm operating a commercial quality program. This method used commercial grade dedication (CGD) as outlined in NQA 1 which had not been applied at this scale. Use of the commercial supply chain was identified as a key factor to the successful completion of SPL. Favorable conditions enabling the use of CGD included: • INL serving as both the designer and the design authority • Design created by an NQA 1 qualified source • A mature CGD program • Availability of a CGD subject matter expert (SME) • A strong construction management program. This white paper elaborates on the methodology employed in the construction of the SPL, the successes achieved, and best practices implemented.

42 - ENGINEERING↗

Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R 2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of riparian enhancement actions in the Columbia River Basin

Riparian enhancement is a common restoration technique in the Columbia River Basin (CRB) and the Pacific Northwest. However, relatively few studies have evaluated its success and even fewer studies include long-term monitoring. Forty-one riparian planting projects located in the CRB, each with a paired treatment and control reach, were evaluated in the summer of 2018 and 2019 using an extensive post-treatment (EPT) design. At each reach, we quantified woody plant abundance, richness, diversity, and vegetation and canopy cover as riparian response variables, and measured terrace height and documented individuals with bud browse, deceased, and with predator protection as potential explanatory variables. Species richness, woody plant abundance (all height classes combined and within shrub height class), and the proportion of woody plants with bud browse or deceased were all higher in treatment than control reaches. However, no significant improvements were observed for any other riparian response or explanatory variables. Implementation techniques, including invasive species removal efforts, follow-up planting, watering, and the type of restoration project (floodplain restoration and planting, in-stream restoration and planting, or solely planting) were also considered as potential explanatory variables and were found to have significant impacts on restoration response for abundance and cover variables. Further, our results suggest that planting implementation methods, site level physical factors, and time since planting all influence the success of riparian planting projects and if not addressed in restoration design and implementation can contribute to a lack of detectable response.

54 ENVIRONMENTAL SCIENCES↗

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗