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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Joint optimization of logistics infrastructure investments and subsidies in a regional logistics network with CO 2 emission reduction targets

This study proposes an optimization model that simultaneously incorporates the selection of logistics infrastructure investments and subsidies for green transport modes to achieve specific CO 2 emission targets in a regional logistics network. The proposed model is formulated as a bi-level formulation, in which the upper level determines the optimal selection of logistics infrastructure investments and subsidies for green transport modes such that the benefit-cost ratio of the entire logistics system is maximized. The lower level describes the selected service routes of logistics users. A genetic and Frank-Wolfe hybrid algorithm is introduced to solve the proposed model. The proposed model is applied to the regional logistics network of Changsha City, China. Findings show that using the joint scheme of the selection of logistics infrastructure investments and green subsidies is more effective than using them solely. In conclusion, carbon emission reduction targets can significantly affect logistics infrastructure investments and subsidy levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions is examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and datasets were examined. A penalized logistic regression model fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at different time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. The methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.

Bramer, L. M.↗
DOE OSTI2012

LOGISTIC FUNCTION PROFILE FIT: A least-squares program for fitting interface profiles to an extended logistic function

The extended logistic function provides a physically reasonable description of interfaces such as depth profiles or line scans of surface topological or compositional features. It describes these interfaces with the minimum number of parameters, namely, position, width, and asymmetry. Logistic Function Profile Fit (LFPF) is a robust, least-squares fitting program in which the nonlinear extended logistic function is linearized by a Taylor series expansion (equivalent to a Newton-Raphson approach) with no apparent introduction of bias in the analysis. The program provides reliable confidence limits for the parameters when systematic errors are minimal and provides a display of the residuals from the fit for the detection of systematic errors. The program will aid researchers in applying ASTM E1636-10, 'Standard practice for analytically describing sputter-depth-profile and linescan-profile data by an extended logistic function,' and may also prove useful in applying ISO 18516: 2006, 'Surface chemical analysis-Auger electron spectroscopy and x-ray photoelectron spectroscopy-determination of lateral resolution.' Examples are given of LFPF fits to a secondary ion mass spectrometry depth profile, an Auger surface line scan, and synthetic data generated to exhibit known systematic errors for examining the significance of such errors to the extrapolation of partial profiles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Impact of the biorefinery size on the logistics of corn stover supply – A scenario analysis

In this study, three scenarios are considered to quantify the impact of the biorefinery size on the required biomass logistical resources. The biorefinery scenarios include small scale (175 dt/day)-SS, medium scale (520 dt/day)-MS and large scale (860 dt/day)-LS. These scenarios are compared against the following logistical resources (1) harvest area and contracted fields, (2) logistics equipment fleet and the workforce to run this fleet and (3) intermediate storage sites and their biomass inventory levels. To this end, the IBSAL-MC simulation model is applied to a corn stover logistics system in Southwestern Ontario. The obtained results show (1) the harvest area and the number of contracted fields increase by 65% and 78% from the SS scenario to the MS and LS scenarios, respectively, (2) the average biomass delivered costs are estimated to be $82.09, $87.49 and $93.75/dry tonne in the SS, MS and LS scenarios. The increase in the capital costs to develop a dedicated logistics equipment fleet are estimated to be far greater than the increase in the delivered costs as the size of the biorefinery increases. The upfront capital costs are estimated to be 6.72 dollars, 21.83 and 35.51 million in these scenarios. To run the logistics equipment fleet efficiently, 37, 136 and 235 well-trained operators are required in the SS, MS ad LS scenarios, respectively, and (3) the inventory level and the land requirement for storage in the MS and LS scenarios are estimated to be 225% and 425% greater than those of the SS scenario. The sensitivity analysis indicates that the logistical resources are highly sensitive to corn yield and farm participation rate. Overall, this study shows the importance of considering the size of the required logistical resources and the associated level of logistical complexity in evaluating the economic viability of a biorefinery project.

09 BIOMASS FUELS↗
DOE OSTI2020

Techno-Economic Impact of Diesel Fuel, Labor, and Interest Rates on Bulk-Format and Round Bale Logistics Expenses for Switchgrass

Highlights System-wide sensitivity of bulk-format and round bale logistics responded to different degrees of expense inputs. Biomass size-reduction expenses for bulk-format were consistently less than round-bale chopping. Stack/reclaim operations with high-density-capacity equipment for bulk-format were the highest expenses. Clean-sheet design of stacker/reclaimer and self-compacting bulk trailer may significantly reduce expenses. Abstract . Deterministic cost analyses were conducted for a harvest, storage, preprocessing, and supply system providing 371,870 dry Mg (dMg) year-1 of milled switchgrass (SG) to a biorefinery from 21,929 ha of production fields within 72 km of the biorefinery. Varied input costs of diesel fuel, labor, and interest rate were input into a highly detailed cost analysis for bulk-format and baseline round bale logistics. These operational input factors, potentially reflecting an evolving economic climate or paradigm shift, were examined to provide insight into the cost to deliver preprocessed biomass feedstock for centralized commercial-scale conversions. Total annual costs per dry unit of SG were determined for all combinations of diesel fuel prices of $0.53 L-1, $0.92 L-1, and $1.32 L-1; total labor costs of $20.00 h-1, $28.85 h-1, and $40.00 h-1 singly and uniformly applied across all labor inputs; and three representative interest rates of 6%, 8%, and 12%. Increases in total cost most depended on increases in diesel fuel cost, followed by labor rate, and finally interest rate. Increases in fuel costs from $0.53 L-1 to $1.32 L-1 yielded a total cost increase of about $11.56 dMg-1 and $13.36 dMg-1 for bulk-format and round bale logistics, respectively, for all combinations of labor and interest rates. The overall increase in labor rate ($20.00 h-1 to $40.85 h-1) resulted in increased total costs of about $10.32 dMg-1 for bulk-format logistics and $9.94 dMg-1 for round bale logistics for all fuel and interest rates. The overall increase in interest rate (6% to 12%) resulted in increased total costs of about $6.72 dMg-1 for bulk-format logistics and $4.21 dMg-1 for round bale logistics for all fuel and labor rates. Increases in total costs for combined increases in fuel cost, labor rate, and interest rate were $28.60 dMg-1 and $27.48 dMg-1, yielding maximum total costs of $87.87 dMg-1 and $86.53 dMg-1 for bulk-format and round bale logistics, respectively. Costs were determined for existing equipment systems, including novel use of waste compaction and ejector semi-trailers. The highest potential for cost reductions may require clean-sheet equipment designs specifically tailored for SG, such as forage harvesters that direct-cut standing SG, mobilized stacker-reclaimer technology to not inhibit stack-area footprint, self-compacting ejector trailer technology, and bale grinding technology incorporating controlled mass feeding and shear failure elements. Keywords: Bales, Bioenergy, Bulk-format, Densification, Field chop, Logistics, Transportation

Agriculture↗
DOE OSTI2022

Logistic Regression in Clinical Studies

• A logistic regression model is used when the outcome of interest is binary. The term “logistic” refers to the underlying “logit” (log odds) function that is used to model the binary outcome. • Odds ratios are produced from a logistic regression model and have a useful interpretation. • Tips, tricks and concepts used to fit logistic regression models are similar to those used in linear regression models. • Modeling building that is knowledge-based rather than automatic is preferred in most applications of logistic regression. • A logistic regression model that is overparameterized (ie, too many variables for too few events) can result in odds ratios that are implausibly large and confidence intervals that are wide and uninterpretable. These types of “overfitted” models should be avoided. • Logistic regression models can be fit using most standard statistical software.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Managing work flow and logistic at waste processing facilities using the waste compliance and tracking system - 15392

Work flow and logistics at a busy radioactive waste processing complex or permitted treatment, storage, and disposal facility (TSDF) can pose a monumental challenge. An efficient operation requires good communication between engineering, logistics, and waste operators. The Los Alamos National Laboratory (LANL) has implemented an application that facilitates seamless communication of work flow requirements, between engineering, logistics, and waste operations personnel in the field. The Waste Compliance and Tracking System (WCATS), a comprehensive waste management system designed at LANL, provides four key elements to support logistics: (a) the container work path, (b) directed unit operation requests, (c) notification of pending operations, and (d) real-time status tools for office and field workers. The combination of these elements allows everyone to function as a team, with a shared knowledge of what is needed to accomplish facility objectives. The first element is like a road map indicating which unit operations are needed and in what sequence they should be performed; this is referred to as a 'work path'. It automatically routes a waste item or container from operation to operation. For example, a given work path might indicate that waste items require radiological survey, radioassay, and a technical review, in that order. When the work path is assigned to a container, the system enforces the correct order of operations. Directed unit operation 'requests', the second element, fills a gap between pre-planned, formal 'work path' activities and the need for flexibility to direct preparatory operations or deal with unexpected issues, like staging or mining containers in preparation for a shipment or transferring containers from one storage unit to another to clear a path for building maintenance. Logistics engineers prepare these 'requests', and the system monitors the status and completion of the work. The third element, notifications, allows team members to subscribe to and receive notice that an operation is pending, initiated, or complete. This functionality supports a range of communication options, including e-mail, cell phone, pager, or application in-box messaging. Notifications allow waste operations personnel to multi-task, and remain in the loop on the status of facility-wide activities. Finally, the fourth element provides tools that communicate work path pending operations and directed requests to field workers on their mobile computer, allowing them to mine or pick containers from storage units, and leverage the capabilities of a bar-code scanner to avoid selection mistakes. Oversight and summary tools are provided, allowing logistics personnel to monitor work path and request task status, identify work-flow bottlenecks, and maximize the efficiency of waste operations. The Waste Compliance and Tracking System (WCATS) provides an innovative, comprehensive set of tools that allow large-scale radioactive waste processing facilities to manage logistics, maximize efficient use of the workforce, and create a team environment, where everyone from management to the waste handlers have an understanding of the work load and what needs to be accomplished. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Reverse logistics network for municipal solid waste management: The inclusion of waste pickers as a Brazilian legal requirement

Highlights: • We propose a reverse logistics network for MSW involving waste pickers. • A generic facility location mathematical model was validated in a Brazilian city. • The results enable to predict the capacity for screening and storage centres (SSC). • We minimise the costs for transporting MSW with screening and storage centres. • The use of SSC can be a potential source of revenue and a better use of MSW. - Abstract: This study proposes a reverse logistics network involved in the management of municipal solid waste (MSW) to solve the challenge of economically managing these wastes considering the recent legal requirements of the Brazilian Waste Management Policy. The feasibility of the allocation of MSW material recovery facilities (MRF) as intermediate points between the generators of these wastes and the options for reuse and disposal was evaluated, as well as the participation of associations and cooperatives of waste pickers. This network was mathematically modelled and validated through a scenario analysis of the municipality of São Mateus, which makes the location model more complete and applicable in practice. The mathematical model allows the determination of the number of facilities required for the reverse logistics network, their location, capacities, and product flows between these facilities. The fixed costs of installation and operation of the proposed MRF were balanced with the reduction of transport costs, allowing the inclusion of waste pickers to the reverse logistics network. The main contribution of this study lies in the proposition of a reverse logistics network for MSW simultaneously involving legal, environmental, economic and social criteria, which is a very complex goal. This study can guide practices in other countries that have realities similar to those in Brazil of accelerated urbanisation without adequate planning for solid waste management, added to the strong presence of waste pickers that, through the characteristic of social vulnerability, must be included in the system. In addition to the theoretical contribution to the reverse logistics network problem, this study aids in decision-making for public managers who have limited technical and administrative capacities for the management of solid wastes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Estimating the required logistical resources to support the development of a sustainable corn stover bioeconomy in the USA

In this paper, the logistical resources required to develop a bioeconomy based on corn stover in the USA are quantified, including field equipment, storage sites, transportation and handling equipment, workforce, corn growers, and corn lands. These resources are essential to mobilize large quantities of corn stover from corn fields to biorefineries. The logistical resources are estimated over the lifetime of the biorefineries. Seventeen corn-growing states are considered for the logistical resource assessment. Over 6.8 billion gallons of cellulosic ethanol can be produced annually from 108 million dry tons of corn stover in these states. The maximum number of required field equipment (i.e., choppers, balers, collectors, loaders, and tractors) is estimated to be 194 110 units with a total economic value of about 26 billion dollars. In addition, 40 780 trucks and flatbed trailers would be required to transport bales from corn fields and storage sites to biorefineries with a total economic value of 4.0 billion dollars. About 88 899 corn growers need to be contracted with an annual net income of over 2.1 billion dollars. About 1903 storage sites would be required to hold 53.1 million dry tons of inventory after the harvest season. These storage sites would take up about 35 320.2 acres and 4077 loaders with an economic value of 0.4 billion dollars would handle this inventory. The total required workforce to run the logistics operations is estimated to be 50 567. Furthermore, the magnitude of the estimated logistical resources demonstrates the economic and social significance of the corn stover bioeconomy in rural areas in the USA.

09 BIOMASS FUELS↗
DOE OSTI2016

Transport spatial model for the definition of green routes for city logistics centers

This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Analysis of Transportation and Logistics Challenges Affecting the Deployment of Larger Wind Turbines: Summary of Results

There is relatively little literature that characterizes transportation and logistics challenges and the associated effects on U.S. wind markets. The objectives of this study were to identify the transportation and logistics challenges, assess the associated impacts, and provide recommendations for strategies and specific actions to address the challenges. The authors primarily relied on interviews with wind industry project developers, original equipment manufacturers, and transportation and logistics companies to obtain the information and industry perspectives needed for this study. They also reviewed published literature on trends and developments in increasing wind turbine size, logistics, and transportation issues.

17 WIND ENERGY↗
DOE OSTI2026

Optimizing Transportation Networks for E-Waste Reverse Logistics: A Multi-Modal Cost Allocation and Pricing Strategy

The exponential growth of electronic waste (e-waste) poses critical challenges for sustainable reverse logistics and transportation network optimization. This study develops a dual-channel transportation framework for e-waste logistics that integrates dynamic freight pricing, cost allocation mechanisms, and game-theoretic coordination. The model captures interactions between centralized hubs and distributed processing networks, accounting for freight rate elasticity, volume allocation, and capacity constraints. Using Stackelberg game theory and cost-sharing strategies, the framework optimizes transportation efficiency and profit distribution across logistics channels. Numerical simulations show that the dual-channel structure increases centralized hub profit by 226.8% compared to baseline single-channel operations, while boosting total transported volume by 1.2% and nearly doubling freight collector profit under cost-sharing. Scenario analyses across regional infrastructures reveal that network density, policy incentives, and logistics costs shape routing efficiency and profit allocation. These findings suggest that coordinated strategies combining dynamic pricing, targeted infrastructure investment, and strategic cost allocation are needed to design efficient, resilient, and regionally adaptable e-waste transportation systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Physics-guided logistic classification for tool life modeling and process parameter optimization in machining

This paper describes a physics-guided logistic classification method for tool life modeling and process parameter optimization in machining. Tool life is modeled using a classification method since the exact tool life cannot be measured in a typical production environment where tool wear can only be directly measured when the tool is replaced. Here, in this study, laboratory tool wear experiments are used to simulate tool wear data normally collected during part production. Two states are defined: tool not worn (class 0) and tool worn (class 1). The non-linear reduction in tool life with cutting speed is modeled by applying a logarithmic transformation to the inputs for the logistic classification model. A method for interpretability of the logistic model coefficients is provided by comparison with the empirical Taylor tool life model. The method is validated using tool wear experiments for milling. Results show that the physics-guided logistic classification method can predict tool life using limited datasets. A method for pre-process optimization of machining parameters using a probabilistic machining cost model is presented. The proposed method offers a robust and practical approach to tool life modeling and process parameter optimization in a production environment.

Machine learning↗