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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Life cycle assessment and tempo-spatial optimization of deploying dynamic wireless charging technology for electric cars

Dynamic wireless power transfer (DWPT), or dynamic wireless charging technology, enables charging-while-driving and offers opportunities for eliminating range anxiety, stimulating market penetration of electric vehicles (EVs), and enhancing the sustainability performance of electrified transportation. However, the deployment of wireless charging lanes on highways and urban road networks can be costly and resource-intensive. A life cycle assessment (LCA) is conducted here to compare the sustainability performance of DWPT applied in a network of highways and urban roads for charging electric passenger cars. The assessment compares DWPT to stationary wireless charging and to conventional plug-in charging using a case study of Washtenaw County in Michigan, USA over 20 years. The LCA is based on three key sustainability metrics: costs, greenhouse gas (GHG) emissions, and energy burdens, encompassing not only the use-phase burdens from electricity and fuel, but also the upfront deployment burdens of DWPT infrastructure. A genetic algorithm is applied to optimize the rollout of DWPT infrastructure both spatially and temporally in order to minimize life cycle costs, GHG, and energy burdens: (1) spatial optimization selects road segments to deploy DWPT considering traffic volume, speed, and pavement remaining service life (RSL); (2) temporal optimization determines in which year to deploy DWPT on a particular road segment considering EV market share growth as a function of DWPT coverage rate, future DWPT cost reduction, and charging efficiency improvement. Results indicate that optimal deployment of DWPT electrifying up to about 3% of total roadway lane-miles reduces life cycle GHG emissions and energy by up to 9.0% and 6.8%, respectively, and enables downsizing of the EV battery capacity by up to 48%, compared to the non-DWPT scenarios. Roadside solar panels and storage batteries are essential to significantly reduce life cycle energy and GHG burdens but bring additional costs. Breakeven analysis indicates a breakeven year for solar charging benefits to pay back the DWPT infrastructure burdens can be less than 20 years for GHG and energy burdens but longer than 20 years for costs. A monetization of carbon emissions of at least $250 per metric tonne of CO 2 is required to shift the optimal “pro-cost” deployment to the optimal “pro-GHG” deployment. A roadway segment with volume greater than about 26,000 vehicle counts per day, speed slower than 55 miles per hour (1 mile ≈ 1.609 km), and pavement RSL shorter than 3 years should be given a high priority for early-stage DWPT deployment.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1995

The sensitivity of various mode sets for probing differential rotation shear zones

The potential of future data sets from global oscillations network group (GONG) and solar oscillations investigation (SOI) for resolving long-lived azimuthal jets and shearing flows, is investigated. Various artificial data sets are constructed, containing noise resembling that of a one-year observation run. These are inverted using a two dimensional regularized least squares inversion. The ability of this method to form well localized averages of the rotation rate, as measured by the averaging kernels, is investigated using an extensive mode set and subsets. It is shown that it is possible to keep the noise in the solution down to a few nHz in much of the solar interior, while obtaining a reasonable resolution for a GONG-like data set. At low latitudes in the middle of the convection zone, an angular resolution of less than 10 deg and a radial resolution of about 0.04 solar radii, are obtained. The averaging kernels depend on the mode set, and a reduction in the number of modes tends to introduce small-scale near surface structures into the averaging kernels which would adversely affect the inferred rotation rate.

Christensen-Dalsgaard, Joergen↗
DOE OSTI2015

Bus.py: A GridLAB-D Communication Interface for Smart Distribution Grid Simulations

As more Smart Grid technologies (e.g., distributed photovoltaic, spatially distributed electric vehicle charging) are integrated into distribution grids, static distribution simulations are no longer sufficient for performing modeling and analysis. GridLAB-D is an agent-based distribution system simulation environment that allows fine-grained end-user models, including geospatial and network topology detail. A problem exists in that, without outside intervention, once the GridLAB-D simulation begins execution, it will run to completion without allowing the real-time interaction of Smart Grid controls, such as home energy management systems and aggregator control. We address this lack of runtime interaction by designing a flexible communication interface, Bus.py (pronounced bus-dot-pie), that uses Python to pass messages between one or more GridLAB-D instances and a Smart Grid simulator. This work describes the design and implementation of Bus.py, discusses its usefulness in terms of some Smart Grid scenarios, and provides an example of an aggregator-based residential demand response system interacting with GridLAB-D through Bus.py. The small scale example demonstrates the validity of the interface and shows that an aggregator using said interface is able to control residential loads in GridLAB-D during runtime to cause a reduction in the peak load on the distribution system in (a) peak reduction and (b) time-of-use pricing cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Wellbore Leakage Mitigation Using Advanced Mineral Precipitation Strategies (Final Scientific/Technical Report)

This research project, entitled Wellbore Leakage Mitigation using Advanced Mineral Precipitation Strategies, was directed toward advancing mineral precipitation technologies to seal wellbore leaks and other potential carbon dioxide (CO 2 ) leakage pathways, including compromised wellbore cement and fracture networks of varying geometries throughout the wellbore and surrounding formation. The advanced mineral sealing techniques were evaluated in the laboratory and the field to expand the range of temperature, pressure, and chemical conditions where mineral precipitation could be used. Rates of enzymatically or thermally induced calcium carbonate precipitation (EICP, TICP) were determined as well as rates of enzyme inactivation at elevated temperatures (>60 °C). Immobilization was shown to enhance the thermal stability of urease enzyme and provide protection from inhibition in low pH conditions. Mineral seals promoted by EICP and TICP were used to seal fractured composite (cement/sandstone) and shale cores in high pressure reactors operated at temperatures greater than 55 °C and 130 °C, respectively. A computational model was updated to model processes of EICP and TICP. The work resulted in a successful field test, which showed that EICP in the presence of low pH fluids (CO 2 -impacted brine) could promote permeability reduction and seal a channel in the near-wellbore environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗
DOE OSTI2022

Image feature extraction and galaxy classification: a novel and efficient approach with automated machine learning

ABSTRACT In this work, we explore the possibility of applying machine learning methods designed for 1D problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly steps, such as the point spread function deconvolution and the training and application of complex Convolutional Neural Networks of thousands or even millions of parameters. In our approach, we extract features from the galaxy images by analysing the elliptical isophotes in their light distribution and collect the information in a sequence. The sequences obtained with this method present definite features allowing a direct distinction between galaxy types. Then, we train and classify the sequences with machine learning algorithms, designed through the platform Modulos AutoML. As a demonstration of this method, we use the second public release of the Dark Energy Survey (DES DR2). We show that we are able to successfully distinguish between early-type and late-type galaxies, for images with signal-to-noise ratio greater than 300. This yields an accuracy of $86{{\ \rm per\ cent}}$ for the early-type galaxies and $93{{\ \rm per\ cent}}$ for the late-type galaxies, which is on par with most contemporary automated image classification approaches. The data dimensionality reduction of our novel method implies a significant lowering in computational cost of classification. In the perspective of future data sets obtained with e.g. Euclid and the Vera Rubin Observatory, this work represents a path towards using a well-tested and widely used platform from industry in efficiently tackling galaxy classification problems at the peta-byte scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Picosecond Optical MCPI-Based Imagers

We present the desired performance specifications for an advanced optical imager, which borrows practical concepts in high-speed microchannel plate (MCP) intensified x-ray stripline imagers and time-dilation techniques. With a four-fold speed improvement in state-of-the-art high-voltage impulse drivers, and novel atomic-layer deposition MCPs, we tender a design capable of 5 ps optical gating without the use of magnetic field confinement of the photoelectrons. We analyze the electron dispersion effects in the MCP and their implications for gating pulses shorter than the MCP transit time. We present a wideband design printed-circuit version of the Series Transmission Line Transformer (STLT) that makes use of 50-ohm coaxial 1.0 mm (110 GHz) and 1.85 mm (65 GHz) hermetically sealed vacuum feedthroughs and low-dispersion Teflon/Kapton circuit materials without the use of any vias. The STLT matches impedance at all interfaces with a 16:1 impedance (4:1 voltage) reduction, and delivers a dispersion-limited sharp impulse to the MCP strip. A comparison of microstrip design calculations is given, showing variances between method of moments, empirical codes, and finite element methods for broad, low-impedance traces. Prototype performance measurements are forthcoming.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning (RAPID)

X-ray ptychographic tomography is a nondestructive method for three dimensional (3D) imaging with nanometer-sized resolvable features. The size of the volume that can be imaged is almost arbitrary, limited only by the penetration depth and the available scanning time. Here we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned priors. The proposed 3D reconstruction method “RAPID” relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground truth. It is then trained to reproduce equal fidelity from much fewer angles. After training, it performs with similar fidelity on the hitherto unexamined portions of the object, previously not shown during training, with a limited set of acquisitions. In our experimental demonstration, the nominal number of angles was 349 and the reduced number of angles was 21, resulting in a x140 aggregate speedup over a volume of 4.48 x 93.18 x 3.92 μm 3 and with (14nm) 3 feature size, i.e. ~ 10 8 voxels. RAPID’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic way. We found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’ range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.

47 OTHER INSTRUMENTATION↗
NASA NTRS2008

Algorithm Optimally Orders Forward-Chaining Inference Rules

People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.

James, Mark↗
NASA NTRS2015

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Variability↗
DOE OSTI2015

Effectiveness of an in-situ permeable reactive barrier in removing strontium-90 from groundwater - 15418

An in-situ permeable reactive barrier (PRB) is being used to remove strontium-90 from groundwater along the 100-N Area shoreline at the U.S. Department of Energy Hanford Site in southeastern Washington. The PRB was formed by emplacing apatite, a calcium phosphate mineral, in the subsurface sediments via injection of calcium-citrate and sodium-phosphate solution into the aquifer through a network of vertical wells. The relatively slow biodegradation of citrate allowed sufficient time for the injected solution to disperse in the PRB treatment zone as the free calcium and phosphate combined to form apatite. Substitution of strontium for calcium in the apatite crystal structure is thermodynamically favorable. As groundwater flows through the PRB toward the Columbia River, strontium-90 is sequestered into the apatite crystal matrix. The sequestered strontium-90 undergoes radioactive decay in place within the PRB. Groundwater monitoring wells installed between the PRB and the Columbia River are used to monitor the PRB effectiveness. The concentration of strontium-90 in the monitoring wells following apatite emplacement are compared to the pre-injection concentrations. The performance goal of the PRB is to reduce the concentration of strontium-90 in groundwater down gradient of the PRB by 90 percent, compared to the pre-injection concentrations. Groundwater samples in Fall 2013 show the percent reduction in strontium-90 concentrations ranged from 71 to 98 percent in eleven of the twelve monitoring wells. The data indicate that the PRB is effective in reducing the flux of strontium-90 toward the Columbia River and is thereby instrumental in protection of the Columbia River. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

A novel approach to criticality accident detection for a legacy facility

For operations on the Sellafield site involving fissile material a Criticality Accident Alarm System (CAAS) has traditionally been installed unless an omission case can be made. An omission case would examine if, in the absence of all controls, a criticality could reasonably be expected or whether the potential dose to an operator would remain below a maximum acceptable dose. It is a UK legal requirement for adequate emergency arrangements to be in place for hazards on a nuclear licensed site. For facilities where criticality is credible there is a regulatory expectation that a -Criticality Warning System- should be in place. A -Criticality Warning System- is not necessarily a full CAAS and alternative means of criticality detection may be part of an adequate emergency plan. The Sellafield site has a Magnox fuel reprocessing facility which has been operated since the 1960's. Evaporation of the Medium Active (MA) liquid waste from this process is undertaken in an associated building. Following extensive review of the plant and process a number of maloperations which can route fissile material to the MA evaporator were identified. Adequate controls to prevent these scenarios were shown to be in place. In the unlikely event of a failure of controls leading to sustained loss of fissile material a criticality incident may occur and hence an emergency plan was determined to be necessary. The novel emergency arrangements which were developed utilized the existing gamma monitor network located across multiple building floors. These gamma monitors are present for radiological safety. This emergency arrangement would require rapid interpretation of the gamma alarms by an operator and the manual triggering of a criticality evacuation alarm. The gamma monitors were demonstrated to be able to detect the minimum incident of concern (10{sup 15} fissions) as well as being able to alarm during the ramp up in power of a large criticality incident (10{sup 18} fissions). It was shown that a criticality accident could readily be distinguished from a radiological event (e.g. loss of containment). To support this work, criticality excursion analysis was used to examine the likely characteristics of a criticality in the MA evaporator. This novel arrangement was justified due to a number of factors including: the limited remaining operational lifetime of this facility (<5 years), the low frequency of maloperation coupled with a failure of controls and the crucial risk reduction provided by the continued reprocessing of Magnox fuel. Furthermore, the time and cost involved with design and installation of a standard CAAS would be substantially greater than a plan based upon existing instrumentation. These arguments were accepted by the UK regulator the Office for Nuclear Regulation (ONR). (author)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

PlumeSeeker{sup TM}: A Model-Based Least-Cost Monitoring Network Design Technology for 3-D Contaminant Plume Boundary Delineation - 19582

Delineating the extent of contamination in an aquifer is a pre-requisite for designing remediation schemes as well as for satisfying regulators and stakeholders. Contaminant plumes are typically delineated using either monitoring well locations with observed concentrations below remedial goals or with computer-drawn contour maps based on available concentration measurements in the groundwater. Computer-generated plume information lacks ground truth resulting in uncertainty about the true limits of contamination. The location of groundwater delineation wells is usually chosen solely based on professional judgement and experience. Both approaches can be inefficient, risky and often unnecessarily expensive. PlumeSeeker{sup TM} is a software-based technology well-suited for the optimal delineation of radiological or emerging contaminant plumes with single or multiple source locations. The software is an enhancement of a university research code for plume delineation using geostatistical and stochastic modeling tools integrated with the widely used groundwater flow and transport modeling software MODFLOW-SURFACT{sup TM}. PlumeSeeker{sup TM} increases the overall confidence in the location and geometry of the plume boundary through the sequential (i.e. a rank-ordered listing) or batch (i.e. a suite of multiple wells) selection of existing or new monitoring wells based on the criteria of maximizing plume boundary uncertainty reduction and on new field information. Using PlumeSeeker{sup TM}, remediation managers can optimally locate new wells at sites where well installation costs are high or hydrogeology is complex. Applicable at sites with or without existing monitoring wells, PlumeSeeker{sup TM} is particularly powerful for optimally allocating project resources (labor, well installation, and laboratory costs) between existing wells and sampling at new locations. An application of PlumeSeeker{sup TM} at a DoD installation demonstrates how the cost of delineating a plume can be minimized. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Multilane Automated Driving With Optimal Control and Mixed-Integer Programming

Road vehicle lane changes often initiate traffic disturbances and can therefore impact road networks’ energy and time efficiency. Furthermore, unexpected changes in traffic conditions may also render lane changes counterproductive for the lane-changing vehicle. Vehicle-to-vehicle connectivity combined with anticipative control could address these challenges via improved lane change decisions by automated vehicles. In a move toward this objective, receding horizon control cast as a mixed-integer quadratic program is used to plan lane changing and acceleration in a coupled optimization. A long-term pacing module, based on Pontryagin’s minimum principle from optimal control theory, sets terminal and input references for receding horizon control to target a user’s expected travel time. To remove nonlinear vehicle dynamics from the receding horizon controller, lane change commands are passed to a pure pursuit steering module whose response is approximated by a second-order linear model. Here, comparison against a rule-based reactive algorithm in arterial and highway scenarios shows an 8.9%–13.7% reduction in energy consumption and a 5.2%–10.3% reduction in the travel time, along with navigational improvements.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Characterization of Acoustic Emissions From Analogue Rocks Using Sparse Regression‐DMDc

Abstract Moisture loss in rock is known to generate acoustic emissions (AE). Phenomena that result in AE during drying are related to the movement of fluids through the pores and induced‐cracks that arise from differential mineral shrinkage, especially in clay‐bearing rock. AE from the movement of fluids occurs from the reconfiguration of fluid interfaces during drying, while AE from mineral shrinkage involves the debonding within or between minerals. Here, analogue rock samples were used to examine the differences in the AE signatures when one or both AE source‐types are present. An unsupervised sparse regression model, Dynamic Mode Decomposition with control, that extends Dynamic Mode Decomposition is used to characterize the AE signals recorded during the drying of porous analogue rock samples fabricated with ordinary Portland cement, with and without clay. This method can effectively and accurately reconstruct acoustic signals emitted from samples that only experience moisture loss without cracking. However, the method struggles to reconstruct signals from samples with intricate crack networks that formed during drying because AE generating mechanisms can emit contemporaneously, and the resulting waves propagate through drying‐induced cracks that can lead to multiple internal reflections. Thus, the differential reconstruction accuracy of time series generated by different underlying physical processes provides a robust filter for reducing large data catalogs. In general, both dynamics and sparse initiating events are learned directly from data and this method exposes a data hierarchy based on the complexity of the intrinsic dynamics.

58 GEOSCIENCES↗
DOE OSTI2015

Dynamics and heterogeneity of a fate determinant during transition towards cell differentiation

Yan is an ETS-domain transcription factor responsible for maintaining Drosophila eye cells in a multipotent state. Yan is at the core of a regulatory network that determines the time and place in which cells transit from multipotency to one of several differentiated lineages. Using a fluorescent reporter for Yan expression, we observed a biphasic distribution of Yan in multipotent cells, with a rapid inductive phase and slow decay phase. Transitions to various differentiated states occurred over the course of this dynamic process, suggesting that Yan expression level does not strongly determine cell potential. Consistent with this conclusion, perturbing Yan expression by varying gene dosage had no effect on cell fate transitions. However, we observed that as cells transited to differentiation, Yan expression became highly heterogeneous and this heterogeneity was transient. Signals received via the EGF Receptor were necessary for the transience in Yan noise since genetic loss caused sustained noise. Since these signals are essential for eye cells to differentiate, we suggest that dynamic heterogeneity of Yan is a necessary element of the transition process, and cell states are stabilized through noise reduction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

Algorithm for Aligning an Array of Receiving Radio Antennas

A digital-signal-processing algorithm (somewhat arbitrarily) called SUMPLE has been devised as a means of aligning the outputs of multiple receiving radio antennas in a large array for the purpose of receiving a weak signal transmitted by a single distant source. As used here, aligning signifies adjusting the delays and phases of the outputs from the various antennas so that their relatively weak replicas of the desired signal can be added coherently to increase the signal-to-noise ratio (SNR) for improved reception, as though one had a single larger antenna. The method was devised to enhance spacecraft-tracking and telemetry operations in NASA's Deep Space Network (DSN); the method could also be useful in such other applications as both satellite and terrestrial radio communications and radio astronomy. Heretofore, most commonly, alignment has been effected by a process that involves correlation of signals in pairs. This approach necessitates the use of a large amount of hardware most notably, the N(N - 1)/2 correlators needed to process signals from all possible pairs of N antennas. Moreover, because the incoming signals typically have low SNRs, the delay and phase adjustments are poorly determined from the pairwise correlations. SUMPLE also involves correlations, but the correlations are not performed in pairs. Instead, in a partly iterative process, each signal is appropriately weighted and then correlated with a composite signal equal to the sum of the other signals (see Figure 1). One benefit of this approach is that only N correlators are needed; in an array of N much greater than 1 antennas, this results in a significant reduction of the amount of hardware. Another benefit is that once the array achieves coherence, the correlation SNR is N - 1 times that of a pair of antennas.

Rogstad, David↗
DOE OSTI2014

A Multi-Objective, Hub-and-Spoke Supply Chain Design Model For Densified Biomass

In this paper we propose a model to design the supply chain for densified biomass. Rail is typically used for long-haul, high-volume shipment of densified biomass. This is the reason why a hub-and-spoke network structure is used to model this supply chain. The model is formulated as a multi-objective, mixed-integer programing problem under economic, environmental, and social criteria. The goal is to identify the feasibility of meeting the Renewable Fuel Standard (RFS) by using biomass for production of cellulosic ethanol. The focus in not just on the costs associated with meeting these standards, but also exploring the social and environmental benefits that biomass production and processing offers by creating new jobs and reducing greenhouse gas (GHG) emissions. We develop an augmented ?-constraint method to find the exact Pareto solution to this optimization problem. We develop a case study using data from the Mid-West. The model identifies the number, capacity and location of biorefineries needed to make use of the biomass available in the region. The model estimates the delivery cost of cellulosic ethanol under different scenario, the number new jobs created and the GHG emission reductions in the supply chain.

09 BIOMASS FUELS↗