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At least 1,009 records · Page 56

Long‐term yields in annual and perennial bioenergy crops in the Midwestern United States

Abstract Many yield predictions in perennial bioenergy species have been made based on data collected during the establishment phase of growth or a limited number of long‐term studies. Few studies compare multiple perennial crops with the dominant agricultural vegetation of the landscape over long time periods. Here, we present the results of 11 years of perennial crop management on fertile agricultural soils in central Illinois, compared with conventional row crop maize/soybean ( Zea mays L., Glycine max L.) production. We examined the long‐term productivity and drought susceptibility of Miscanthus x giganteus Greef et. Deu. ex. Hodkinson et Renvoize (miscanthus), Panicum virgatum L., Cave‐in‐Rock cultivar (switchgrass), and a native prairie mix, in contrast to annual maize/soybean agriculture. Long‐term yields for miscanthus and switchgrass failed to reach initial predictions made during the establishment phase; however, in miscanthus, the 11 th year of production shows little progressive yield loss with age, exceeding the modeled limit for the onset of age‐related decline. Harvest timing and differences in yields from hand and machine harvests in perennial crops likely contribute to overestimates of potential yields. Application of fertilizer to mature miscanthus resulted in significant increases in yield after a severe drought, though modeled effects of management and drought in miscanthus point to a more complex mechanism for yield response.

09 BIOMASS FUELS↗

Modeling of Sandwich Sheets with Metallic Foam

World-wide vehicles safety experts agree that significant further reductions in fatalities and injuries can be achieved as a result of the use of new lightweight and energy absorbing materials. On this work, the authors present the development and evaluation of an innovative system able to perform reliable panels of sandwich sheets with metallic foam cores for industrial applications. The mathematical model used to describe the behavior of sandwich shells with metal cores foam is presented and some numerical examples are presented. In order to validate those results mechanical experiments are carried out. Using the crushable foam constitutive model, available on ABAQUS, a set of different mechanical tests were simulated. There are two variants of this model available on ABAQUS: the volumetric hardening model and the isotropic hardening model. As a first approximation we chose the isotropic hardening variant. The isotropic hardening model available uses a yield surface that is an ellipse centered at the origin in the p-q stress plane. Based on this constitutive model for the foam, numerical simulations of the tensile and bulge test will be conducted. The numerical results will be validated using the data obtained from the experimental results.

36 MATERIALS SCIENCE↗

Techno-Economic Case Study: Low-Temperature Conversion Performance Based on Isolated Anatomical Fractions of Corn Stover

This report summarizes analysis conducted to support a case study under the Feedstock-Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the yield and cost ramifications for processing isolated anatomical fractions of corn stover through a low-temperature conversion (biochemical pathway) biorefinery. It is hypothesized that different individual anatomical fractions of corn stover vary in composition and recalcitrance, such that processing each fraction on its own e.g. through dedicated campaigns may enable economic benefits relative to processing the whole stover material. To investigate this concept, we worked with FCIC researchers to obtain data on compositional analysis, as well as processing conditions and yields, for conversion of whole corn stover plus three individual anatomical fractions (cobs, husks, and stalks) across key steps of the biorefinery conversion process within FCIC research scope, namely pretreatment and enzymatic hydrolysis. After running the data through the TEA models, fractionated cobs and husks achieved higher fuel yields and lower minimum fuel selling prices than whole corn stover, but stalks fared worse than whole stover on both metrics. The most direct takeaway from this assessment is that a biorefinery would stand to benefit economically from maximizing the use of cob and husk fractions while avoiding or minimizing the use of stalks, though recognizing practical constraints with this approach in maintaining an equivalent processing capacity (fixed at 2,000 dry metric tonne per day in all cases).

09 BIOMASS FUELS↗

Improving the Transportability of a Deep Learning Denoising Model Using Transfer Learning Techniques

The adoption of machine learning techniques in the seismology community has led to great performance improvements in several areas, including signal processing. Specifically, the development of deep learning–based seismic waveform denoising models has the potential to yield improvements in signal detection capabilities for networks operating in particularly noisy environments. Recent advancements in the design of these deep learning denoising models have included the incorporation of continuous and discrete wavelet transform functions into the network architecture to improve the learning capabilities and efficiency of said models. These wavelet transform–based seismic denoising models have shown improved denoising capabilities in regions where there is good agreement between the data features present in the training and evaluation datasets. However, questions remain about the overall transportability of these models to other monitoring regions. Here, in this study, we will determine the baseline transportability of a newly developed multilevel wavelet‐transform convolutional neural network (MWCNN) seismic denoising model. We accomplish this by taking a version of the MWCNN denoising model trained on data collected from the Utah region and evaluating its denoising performance on datasets collected from the neighboring Nevada region, which differ with regard to monitoring sensor types and event histories. We find that there is a notable variability in denoising performance related to the degree of similarity between the initial and new target datasets. The most notable difference in denoising performance is the ability of the denoising model to preserve accurate amplitude information associated with the signal energy present in the waveform data. Finally, we evaluate the ability of transfer learning techniques to improve the transportability of the MWCNN denoising model. We find that although there is still a performance gap present in the denoising results of the MWCNN model, transfer learning did yield improved results.

Quinones, Louis [Sandia National Laboratories (SNL↗

Automated Operational Forecasting of Monsoon Low Pressure Systems

Monsoon low pressure systems (LPSs) are the dominant rain-bearing weather system of South Asia, often producing extreme precipitation and hydrological disasters in a region inhabited by nearly two billion people. Despite the importance of these storms, no operational system has automatically identified and tracked LPS in real time in numerical weather prediction model output; many commonly used vortex-tracking algorithms are ill suited for monsoon LPS because of the weak winds and cold cores of these systems. Here, we describe a new system that uses optimized algorithms to identify monsoon LPS in short- to medium-range forecasts from the U.S. Global Ensemble Forecast System (GEFS) and a version of the deterministic Global Forecast System (GFS) adapted and used operationally by the Indian Institute of Tropical Meteorology (IITM). We also assess the historical performance of these models in forecasting South Asian monsoon LPS, comparing this with the performance of the Integrated Forecasting System of the ECMWF. We assess the accuracy of model predictions of LPS genesis, position, intensity, and precipitation rates for forecast lead times of 1–5 days, yielding quantitative information on model biases to guide operational forecasters and disaster managers. The system we introduce here could be extended to other low-latitude regions affected by dynamically weak, heavily precipitating atmospheric vortices that are often not included in tropical cyclone inventories.

54 ENVIRONMENTAL SCIENCES↗

13 C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined 13 C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Yarrowia lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption. These genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg/L of free fatty acids. With the addition of ATP citrate lyase and downregulation of malate synthase, the engineered strain produced 26% more free fatty acids. Further increases in free fatty acid production of 33% were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by ~70%.

-omics data↗

$\mathcal{g}$ modes of neutron stars with hadron-to-quark crossover transitions

Here we perform the first study of the principal core g-mode oscillation in hybrid stars containing quark matter, utilizing a crossover model for the hadron-to-quark transition inspired by lattice QCD. The ensuing results are compared with our recent findings of g-mode frequencies in hybrid stars with a first-order phase transition using Gibbs constructions. We find that models using Gibbs construction yield g-mode amplitudes and the associated gravitational energy radiated that dominate over those of the chosen crossover model owing to the distinct behaviors of the equilibrium and adiabatic sound speeds in the various models. Based on our results, we conclude that were g modes to be detected in upgraded LIGO and Virgo detectors it would indicate a first-order phase transition akin to a Gibbs construction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Small Volume Fuel Testers Report

Micro-liter fuel ignition testing (μ-FIT) is based on the premise that characteristics FREI (Flames with Repetitive Extinction and Ignition, i.e. cyclically occurring combustion events within heated capillaries), are linked to fuel properties. In early FY16, proof-of-concept measurements with primary reference fuel (PRF) mixtures, i.e. blends of n-heptane and iso-octane, yielded clear evidence for the feasibility of the approach. Our experiments showed that it is critical to accurately link observed flame positions to local temperatures, which provides information on ignition, extinction and flame propagation, all of which are known to be impacted by fuel properties. In FY16, one major hurdle was uncertainty of temperature calibration, which required significant efforts for corrective action that were not included in the original scope of work. Temperature calibrations are obtained by translating a thermocouple within the capillary in absence of a flame. While measurements have good repeatability when accounting for transient and insertion effects, results from nominally identical thermocouples reveal unacceptable uncertainty (up to ±50K), which is attributed to variations in thermocouple placement and manufacturing tolerances. This issue is currently being resolved by switching to non-intrusive optical temperature measurements. Updates are expected to yield uncertainties of less than ±10K, while also eliminating transient and insertion effects. The experimental work was complemented by computational efforts where it was shown that a simplified Lagrangian zero-D model with detailed kinetics yields fuelspecific differentiation of ignition temperatures for simple fuels that are consistent with experiments. Further, a 2D transient model was implemented in OpenFOAM to investigate combustion behavior of simple fuels at elevated pressure. In an upcoming visit to LLNL, more advanced simulations using LLNL’s computational tools (e.g. zero-RK) are planned, which will yield additional numerical insights on FREI behavior of more realistic spark ignited (SI) engine fuel surrogates. As there is a lag between DOE FY16 and the time frame of the LSU subcontract, it is anticipated that deliverables outlined in the scope of work will be met by the end of the subcontract (January 2017).

30 DIRECT ENERGY CONVERSION↗

Multicomponent Nonlinear Systems of Bose-Fermi Fields: Exact Solutions

We present families of stationary solutions for a multicomponent nonlinear system of two boson and N{sub f} fermion fields in terms of elliptic functions of modulus k. This system is an extention of models, describing Bose-Fermi mixtures in the mean field approximation. We also single out the particular cases when the quasiperiodic solutions become periodic ones. In the limit of sinusoidal external potential (k{yields}0) our solutions model periodic waves trapped in an optical lattice. The other limit k{yields}1 provides solutions expressed by hyperbolic functions (vector solitons). Thus we demonstrate that our system describes quasi-periodic and periodic waves, as well as solitons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

235 U(n, f) Independent fission product yield and isomeric ratio calculated with the statistical Hauser–Feshbach theory

In this work, we have developed a Hauser–Feshbach fission fragment decay model, HF 3 D, which can be applied to the statistical decay of more than 500 primary fission fragment pairs (1,000 nuclides) produced by the neutron induced fission of 235 U. The HF 3 D model numerically integrates fission fragment yield and their initial excitation energy, spin and parity distributions for these 1,000 nuclides. The fission fragment yield Y ( A ) and the total kinetic energy are model inputs, and we estimate them from available experimental data for the 235 U(n th ,f) system. The model parameters in the statistical decay calculation are adjusted to reproduce some fission observables, such as the neutron emission multiplicity v - , its distribution P ( ν ), and the mass dependence v - ( A ). The calculated fission product yield (FPY) and isomeric ratio (IR) are compared with experimental data. The calculated independent FPY Y I ( A ) at the thermal energy reproduces the experimental data well, while the calculated IRs tend to be lower than the Madland–England model prediction. The HF 3 D model is extended to higher incident neutron energies up to the second-chance fission threshold. We demonstrate for the first time that most of the IRs stay constant, although the production of isomeric state changes as the incident energy increases.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Jagermeyr, Jonas↗

System-Level Optimization to Improve Biofuel Potential via Genetic Engineering and Hydrothermal Liquefaction

The economic success of biofuels and bioproducts depends on system-level optimization including biomass production and conversion. Hydrothermal liquefaction (HTL) can convert wet biomass such as microalgae into a biofuel intermediate (BFI) under elevated temperatures and pressure. An understanding of the impacts of biomass composition on BFI yield and quality can inform genetic engineering strategies in the improvement of biochemical composition for biofuel production. In this work, wild type cyanobacterium Synechocystis sp. PCC 6803 biomass was doped with various common cellular storage compounds in lab-scale HTL experiments. Doping with glycogen or polyhydroxybutyrate (PHB) significantly reduced BFI yields, while doping with triglycerides (TAG) or medium chain-length polyhydroxyalkanoate (mcl-PHA) increased BFI yield and quality. In light of these observations, a genetically engineered Synechocystis strain deficient in glycogen biosynthesis was cultivated to produce biomass for HTL, leading to a 17% increase in BFI yield. In addition, we built a multiphase component additivity (MCA) model that can predict BFI yield and quality with PHAs in the biomass. This work demonstrates an effective strategy to integrate strain development with downstream biomass conversion to maximize biofuel yield, with lessons applicable to microalgae as well as other biomass.

09 BIOMASS FUELS↗

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

54 ENVIRONMENTAL SCIENCES↗

Analysis of Sandwich Shells with Metallic Foam Cores based on the Uniaxial Tensile Test

On this work, the authors present the development and evaluation of an innovative system able to perform reliable panels of sandwich sheets with metallic foam cores for industrial applications, especially in automotive and aeronautical industries. This work is divided into two parts; in the first part the mathematical model used to describe the behavior of sandwich shells with metal cores form is presented and some numerical examples are presented. In the second part of this work, the numerical results are validated using the experimental results obtained from the mechanical experiments. Using the isotropic hardening crushable foam constitutive model, available on ABAQUS, a set of different mechanical tests were simulated. The isotropic hardening model available uses a yield surface that is an ellipse centered at the origin in the p-q stress plane. Using this constitutive model, the uniaxial tensile test for this material was simulated, and a comparison with the experimental results was made.

36 MATERIALS SCIENCE↗

Discrete photon implementation for plasma simulations

The self-produced light emission from pulsed plasma discharges and its impact on plasma development are challenging to characterize through simulation and modeling, chiefly due to the large number of radiating species and limited computer memory. Often, photo-processes, such as photo-ionization or photo-emission of electrons, are implemented through over-simplifying approximations or neglected altogether. Here, a method applicable to plasma simulations is implemented in a Particle-in-Cell /Monte Carlo Collision model, which is capable of discretely tracking photons and their corresponding wavelengths. Combined with the appropriate cross sections or quantum yields, a wavelength dependent model for photo-ionization or photo-emission may be implemented. Additionally, by resolving the wavelengths of each photon, an emission spectrum for a region of interest may be generated. Simulations for a pure nitrogen environment reveal that the calculated emission profile of the second positive system agrees well with the experimental spectrum of a pulsed, nanosecond discharge in the same spectral region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Searches for New Symmetries in pp Collisions with the Razor Kinematic Variables at $\mathbf{\sqrt{s}} =$ 7 TeV

The construction and LHC phenomenology of the razor variables M R , an event-by-event indicator of the heavy particle mass scale, and R, a dimensionless variable related to the transverse momentum imbalance of events and missing transverse energy, are presented. The variables are used in the analysis of the first proton-proton collisions dataset at CMS (35 pb -1 ) in a search for superpartners of the quarks and gluons, targeting indirect hints of dark matter candidates in the context of supersymmetric theoretical frameworks. The analysis produced the highest sensitivity results for SUSY to date and extended the LHC reach far beyond the previous Tevatron results. A generalized inclusive search is subsequently presented for new heavy particle pairs produced in √s = 7 TeV proton-proton collisions at the LHC using 4.7±0.1 fb -1 of integrated luminosity from the second LHC run of 2011. The selected events are analyzed in the 2D razor-space of MR and R and the analysis is performed in 12 tiers of all-hadronic, single and double leptons final states in the presence and absence of b-quarks, probing the third generation sector using the event heavy- flavor content. The search is sensitive to generic supersymmetry models with minimal assumptions about the superpartner decay chains. No excess is observed in the number or shape of event yields relative to Standard Model predictions. Exclusion limits are derived in the CMSSM framework with gluino masses up to 800 GeV and squark masses up to 1.35 TeV excluded at 95% confidence level, depending on the model parameters. The results are also interpreted for a collection of simplified models, in which gluinos are excluded with masses as large as 1.1 TeV, for small neutralino masses, and the first-two generation squarks, stops and sbottoms are excluded for masses up to about 800, 425 and 400 GeV, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

In Situ Tensile Testing of Single Crystal Molybdenum Alloy Fibers with Various Dislocation Densities in a Scanning Electron Microscope

In-situ tensile tests have been performed in a dual beam focused ion beam and scanning electron microscope on as-grown and prestrained single-crystal molybdenum-alloy (Mo-alloy) fibers. The fibers had approximately square cross sections with submicron edge lengths and gauge lengths in the range of 9-41 {mu}m. In contrast to previously observed yield strengths near the theoretical strength of 10 GPa in compression tests of {approx}1-3-{mu}m long pillars made from similar Mo-alloy single crystals, a wide scatter of yield strengths between 1 and 10 GPa was observed in the as-grown fibers tested in tension. Deformation was dominated by inhomogeneous plastic events, sometimes including the formation of Lueders bands. In contrast, highly prestrained fibers exhibited stable plastic flow, significantly lower yield strengths of {approx}1 GPa, and stress-strain behavior very similar to that in compression. A simple, statistical model incorporating the measured dislocation densities is developed to explain why the tension and compression results for the as-grown fibers are different.

36 MATERIALS SCIENCE↗

Novel Microbial Routes to Synthesize Industrially Significant Precursor Compounds

Ethylene is the most widely employed organic precursor compound in industry. The potential to impact ethylene formation via recently discovered microbial processes is tenable using plentiful CO2 feedstocks. The overall long-term objective of this project was to develop an industrially compatible microbial process to synthesize ethylene in high yields. The key objective of this project was to fully define and initially characterized a recently discovered and genetically regulated anaerobic pathway to produce high levels of ethylene called the Dihydroxyacetone Phosphate - Ethylene Pathway in phototrophic bacteria. This was addressed through the following specific aims: 1. Fully probe the catalytic potential of all enzymes of the DHAP ethylene pathway and determine the regulatory mechanism of DHAP-ethylene pathway gene expression. 2. Discover effective and active ethylene enzymes encoded in cultured and uncultured organisms from anoxic environments. 3.Model the thermodynamics and kinetics of ethylene synthetic pathways to guide engineering efforts in integrating best performing DHAP-ethylene pathway enzymes into model bacteria chassis for enhance ethylene yields. Through this project we discovered the initially missing genetic and enzyme component of the DHAP-ethylene pathway that directly synthesized ethylene and other important industrial compounds like methane and ethane from specific substrates. We uncovered and partially characterized a nitrogenase-like reductase that functions in DHAP-ethylene pathway specifically and in methionine synthesis in general. This nitrogenase-like system is called the Methylthio-Alkane Reductase (MAR) for its ability to cleave volatile organic sulfur compounds into methanethiol (CH3-SH) for methionine synthesis and a hydrocarbon byproduct. Key to the DHAP-ethylene pathway, MAR is the essential enzyme that cleaves 2-methylthioethanol (CH3-S-CH2-CH2-OH) into ethylene. Coordinately, we uncovered that the MAR genes and genes associated with conversion of methanethiol (CH3-SH) to methionine are under genetic control of a LysR Type Transcriptional Regulator called SalR, whose activity is dependent upon the amount of sulfate available to the cell. When sulfate as the preferred sulfur source for cell growth drops below 200 micromolar, SalR become active for expressing the MAR and methionine biosynthesis genes to enable the cell to grow from volatile organic sulfur compounds and make ethylene. Metabolic thermos-kinetic modeling revealed that these MAR reactions for ethylene and other hydrocarbon production are highly thermodynamically favorable and are one of the largest driving forces for ethylene production by the DHAP-ethylene pathway for high ethylene yields. Modeling also indicated that a key aldolase and to a lesser extent an isomerase of the DHAP-ethylene pathway for production of the ethylene precursor, 2-methylthioethanol, also would increase ethylene yields. Through metagenomic mining and gene synthesis by the JGI DNA synthesis program, over 500 aldolase and isomerase homologs were synthesized and screened. From this, variants were uncovered with substantially higher activity that increased ethylene yields 5-fold via the aldolase reaction and 1.5-fold via the isomerase reaction. Each of these elements that increase ethylene production were integrated together via plasmid under appropriate gene promoter elements in the phototrophic bacterium, Rhodospirillum rubrum, resulting in at least 3 orders of magnitude increase in ethylene yield from carbon dioxide feedstock.

10 SYNTHETIC FUELS↗