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Optimization of harvest and logistics for multiple lignocellulosic biomass feedstocks in the northeastern United States
A mixed-integer linear programming model was developed to optimize the multiple biomass feedstock supply chains, including feedstock establishment, harvest, storage, transportation, and preprocessing. The model was applied for analyses of multiple biomass feedstocks at county level for 13 states in the northeastern United States. In the base case with a demand of 180,000 dry Mg/year of biomass, the delivered costs ranged from $\$67.90$ to $\$86.97$ per dry Mg with an average of $\$79.58$ /dry Mg. The biomass delivered costs by county were from $\$67.90$ to 150.81 per dry Mg across the northeastern U.S. Considered the entire study area, the delivered cost averaged $\$85.30$ /dry Mg for forest residues, $\$84.47$ /dry Mg for hybrid willow, $\$99.68$ for switchgrass and $\$97.87$ per dry Mg for Miscanthus. Seventy seven out of 387 counties could be able to deliver biomass at $84 per dry Mg or less a target set by US DOE by 2022. A sensitivity analysis was also conducted to evaluate the effects of feedstock availability, feedstock price, moisture content, procurement radius, and facility demand on the delivered cost. Lastly, our results showed that procurement radius, facility capacity, and forest residue availability were the most sensitive factors affecting the biomass delivered costs.
Logistics planning for direct temporary disaster housing assistance under demand uncertainty
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Introducing CRISTAL: A model of collaborative, informed, strategic trade agents with logistics
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Penalized Logistic Regression Likelihood Ratio Test Analysis to Detect Signals of Adverse Events From Interactions in Postmarket Safety Surveillance
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Reanalysis of crackle perception data using logistic and logarithmic fits and sound quality metrics
Mathematical models of human auditory perception (sound quality metrics) are explored for the purpose of fitting human subject data from a prior published study. A variety of linearizing transforms and techniques are employed. Ultimately, a model is identified that predicts 98.9% of the variance in average human subject ratings of crackliness of jet noise waveforms.
Reverse Logistics Ev Battery Recycling Agent Base Model
This represents the initial regional tier of the electric vehicle (EV) battery recycling agent base model. Through this model, we can ascertain the number of EV purchases at both the state and regional levels. We employ census data to develop a diverse household profile to inform decisions regarding the acquisition of new or used EVs. The number of EV purchases at the state level will affect the future demand for recycling, reuse, and repurposing of end-of-life EV batteries. Additionally, tax credits, EV rebate programs, and the financial capacity of households will influence the number of EV purchases, thereby further impacting the demand for EV battery recycling.
Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics
Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.
Port Authority of New York and New Jersey Sustainable Aviation Fuel Logistics and Production Study
The Port Authority of New York and New Jersey (PANYNJ) sustainability commitment is to meet the goals set by the Paris Agreement, with an interim greenhouse gas reduction target of 35% by 2025 and 80% by 2050. PANYNJ is seeking sustainable solutions to reduce carbon emissions for all public forms of transportation, including aviation. Similarly, the global aviation industry adopted the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA), which seeks to cap net carbon dioxide (CO 2 ) aviation emissions at 2020 levels through 2035. Industry has also set a goal of reducing CO 2 emissions by 50% compared to 2005 levels by 2050. Sustainable aviation fuel (SAF), made from non-petroleum feedstocks, is a near-term alternative fuel that reduces emissions from air transportation. The National Renewable Energy Laboratory (NREL) conducted a resource assessment and a techno-economic analysis to identify the potential for production in the port district. Although SAF could be sourced from other areas of the United States or imported, an evaluation of local production was conducted due to the potential positive impacts of a circular economy by converting local waste feedstocks into SAF for use at nearby airports. The study found that the highest volumes of feedstock nearby were municipal solid waste and woody biomass. SAF must be blended with Jet A up to certain percent determined by ASTM International fuel quality standards prior to use in aircraft. SAF from a stand-alone facility could be delivered by barge, rail, or truck to a Linden, New Jersey based terminal for blending with Jet A or it could be blended in the Gulf region and shipped via the Colonial pipeline to one of the terminals. The investment will take place at the terminal(s) to accommodate SAF/Jet A blends and it will be business as usual for the airports in how they receive fuel and distribute it to aircraft.
History of Ethanol Fuel Adoption in the United States: Policy, Economics, and Logistics
Ethanol has the achieved the greatest market share of all the alternative transportation fuels that have been researched, developed, and deployed in the US. There are multiple lessons to be learned from the history of ethanol adoption that can be applied to future fuels and products. Ethanol has replaced portions of gasoline in three main blend levels, with corresponding vehicles, equipment, benefits, and policies. The first is E10, which has replaced nearly all pure gasoline (E0) sold in the United States today (U.S. Energy Information Administration 2015). This was brought about through generations of policies that were motivated by multiple factors related to engine performance, energy security, health, air quality, and climate protection. Ethanol's high octane has been a consistent driver of the fuel because this enables higher performance engines. Early policies (1973-1979) were largely motivated by the desire to reduce dependence on petroleum sourced from members of the Organization of the Petroleum Exporting Countries, or OPEC. Fuel policy in the 1980s was largely in pursuit of promoting octane number enhancers that could replace lead. Criteria pollutant reduction was the overarching goal of actions taken from 1990 to 2005. From 2005 to the present, fuel policy has been largely motivated by energy security and climate protection goals. These policies were usually technology-agnostic and promoted multiple fuels and additives during each period. However, ethanol is the only fuel identified that is cost effective with qualities that enabled it to prosper in the policy environments of all four of these periods.The second market for ethanol is via 85% ethanol (E85). This fuel has the advantage of a greater concentration of ethanol but the disadvantage of not being compatible with regular gasoline vehicles. Instead, it can only be used in flexible-fuel vehicle (FFVs), which can use every blend level from E0 to E85. Therefore, much of the effort to increase E85 consumption has been aimed at incentivizing automakers to manufacture FFVs, drivers to purchase FFVs, and fueling stations to equip themselves to sell E85.The third, and newest, market through which ethanol is consumed is 15% ethanol (E15), which builds upon the E10 market to increase ethanol consumption by common gasoline vehicles. Efforts to create the E15 market consisted largely of testing vehicles and refueling equipment for compatibility, creating waivers to allow the use of E15, placing requirements on E15 retailers, and incentivizing retailers to equip themselves to purchase E15.
Next Generation Logistics Systems for Delivering Optimal Biomass Feedstocks to Biorefining Industries in the Southeastern U.S.
The diverse portfolio of biomass sources that is available in the Southeastern U.S., including a significant supply of pine “residue”, represents a valuable strategic position for the region. Through blends formulated based on critical properties, this project will take full advantage of the range in biomass properties afforded by the portfolio to produce a consistent, high-performance feedstock for the industry, while lowering cost. Key developments being targeted to enable this potential include whole-tree transport to a state-of-the-art merchandising depot that will further access biomass from ongoing, forest industry operations. The approach will more effectively utilize the tree and distribute cost, while minimizing in-woods contamination of the woody biomass component. To implement this vision, information on the chemical composition and changes that are induced during multiple preprocessing steps (size reduction, moisture removal, densification, etc.) is needed. New NIR sensor technology will be developed for online monitoring of important biomass properties. The data will be incorporated into a statistical process control platform to improve process efficiency and meet required specifications. Advanced process models are being developed to inform the techno-economic and life-cycle assessment of the program’s impact. The new system will ultimately reduce operational risks from supply chain disruptions, and allow operation of larger-scale biorefineries.
Experiment Logistics for an International Blind Intercomparison Exercise for Nuclear Accident Dosimetry at Godiva-IV
This document is the Experimental Set-up and Design (CED-3A) Report for IER-538, “Full Dosimetry Exercise Around Godiva Reactors” The report discusses the structure of the exercise consisting of two critical excursions, identifying the participating laboratories and their points of contact. The report also includes details of all dosimetry each laboratory will submit to be placed in proximity to Godiva-IV on aluminum plates or BOMAB phantoms. Each laboratory list the counting and spectroscopy equipment to be utilized at the LLNL NAD Laboratory in Mercury. The exercise is tentatively scheduled for one week in fiscal year 2022.
Developing a Logistic Regression Method for Valuation of Grid-Level Energy Storage Systems.
Abstract not provided.
Logistics of High Throughput Data Transfer in HEP
Explore the source record for details and available documents.
Reanalysis of subjective crackle ratings using a logistic curve fit.
Abstract not provided.
Experiment Logistics for an International Blind Intercomparison Exercise for Nuclear Accident Dosimetry at the Armed Forces Radiobiology Research Institute's TRIGA Reactor
This document is the Experimental Set-up and Design (CED-3a) Report for IER-602, “Dosimetry Exercise with Armed Forces Radiobiology Research Institute (AFRRI) - Exercise” The report discusses the structure of the exercise consisting of three reactor exposures, identifying the participating laboratories and their points of contact. The report also includes details of all dosimetry each laboratory will submit to be placed in proximity to AFRRI on aluminum plates or BOMAB phantoms. Each laboratory lists the counting and spectroscopy equipment to be utilized at AFFRI. The exercise is tentatively scheduled for one week in June, 2024 (FY24 Q4).
Simulation of a Logistically Constrained Stratospheric Aerosol Injection in the Arctic
Presentation for the GeoMIP 2024 Meeting