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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↗

NASA NTRSDate not supplied

Surviving and Thriving in Space and on Earth's Oceans - Human Logistics and Sustainability Comparisons and Considerations

The human species has a yearning for exploration as evidenced by the extensive historical ocean voyages and expeditions which have led to a massive advancement in the scientific and geodetic knowledge about planet Earth. These global explorations via the oceans have also had strategic, economic, cultural and religious implications and impacts, which have drastically changed the state of humanity and its condition. The transportation network created by ships traveling across the oceans has been supplemented by other transportation networks on land and in the air, creating a global economy that, in general, has improved the human condition leading to better health, longer lives, lower child mortality, better education, political freedom, higher gross national product (GNP) and improved hygiene. The logical extension of this societal trend is to extend the transportation network and human civilization into outer space, beyond the cradle of planet Earth. Our solar system contains vast amounts of natural resources which can be harnessed and used to bootstrap a space economy and related infrastructure by using advanced technologies. Sailing journeys from hundreds of years ago required large vessels and large crews, (in comparison with today’s space capsules). Modern sailors of today are able to complete large voyages, in small vessels, with a minimal crew, comparable in magnitude to modern space travel. This paper will use a systems engineering approach (e.g. using the NASA Human Integration Design Handbook (HIDH), NASA-SP-2010-3407, 2010 and the “Advanced Life Support Baseline Values and Assumptions Document, (BVAD)” NASA-CR-2004-208941, 2004.), to examine and compare the logistics and sustainability aspects of a small crew traveling on Earth's oceans in sailing vessels versus humans traveling in space. The “Mālama Honua Worldwide Voyage” of the Hokule’a, a replica of an ancient Hawaiian double hulled sailing canoe, will be used as a case study. This is the best comparison case since the Polynesian exploration of the vast (and virtually empty) Pacific Ocean is the closest analogue to modern space travel. “"Both are voyages of exploration.” –Shuttle astronaut Lacy Veach. Minimizing waste and maximizing re-use and re-cycling will lead to more efficient logistics and sustainability. In addition, In-Situ Resource Utilization (ISRU) strategies, based on successful Earth based strategies used for many years by sailors will be considered and evaluated for their usefulness. For example, human logistics for a typical space mission are shown in Table 1 and Table 2 (Lopez et al, 2015). Studies show that typical human water consumption in space is projected to be 3.2 kg/day per crew member as shown in Table 2. Data from human sailing voyages around the globe will be examined. Anecdotal evidence indicates that knowledgeable and well-equipped modern sailors, who conserve water, can comfortably live using 1.5 to 5 kg/day per person. This paper will investigate key logistics and sustainability aspects of living in space and compare them quantitatively to similar aspects of living on ocean faring sailing vessels on Earth. Mutually beneficial observations, advanced technologies and modern considerations will be applied within confines of a remote sailing environment, which could be of immense value to both the space faring community and the ocean sailing community.

Space↗

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↗

DOE OSTI2021

Logistic classification for tool life modeling in machining

This paper describes the application of logistic classification for tool life modeling and prediction in an industrial setting using shop floor data. Tool life is treated as a classification problem since tool wear can only be measured at the time of tool replacement in a production environment. Laboratory tool wear experiments are used to simulate shop floor wear data by two states: not worn (class 0); and worn (class 1). To incorporate non-linearity in logistic classification, a log-transformation of input features is performed. The logistic classification approach, results, and interpretability of the logistic model are presented.

Karandikar, Jaydeep↗

DOE OSTI2017

Discriminating between adaptive and carcinogenic liver hypertrophy in rat studies using logistic ridge regression analysis of toxicogenomic data: The mode of action and predictive models

Chemical exposure often results in liver hypertrophy in animal tests, characterized by increased liver weight, hepatocellular hypertrophy, and/or cell proliferation. While most of these changes are considered adaptive responses, there is concern that they may be associated with carcinogenesis. In this study, we have employed a toxicogenomic approach using a logistic ridge regression model to identify genes responsible for liver hypertrophy and hypertrophic hepatocarcinogenesis and to develop a predictive model for assessing hypertrophy-inducing compounds. Logistic regression models have previously been used in the quantification of epidemiological risk factors. DNA microarray data from the Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System were used to identify hypertrophy-related genes that are expressed differently in hypertrophy induced by carcinogens and non-carcinogens. Data were collected for 134 chemicals (72 non-hypertrophy-inducing chemicals, 27 hypertrophy-inducing non-carcinogenic chemicals, and 15 hypertrophy-inducing carcinogenic compounds). After applying logistic ridge regression analysis, 35 genes for liver hypertrophy (e.g., Acot1 and Abcc3) and 13 genes for hypertrophic hepatocarcinogenesis (e.g., Asns and Gpx2) were selected. The predictive models built using these genes were 94.8% and 82.7% accurate, respectively. Pathway analysis of the genes indicates that, aside from a xenobiotic metabolism-related pathway as an adaptive response for liver hypertrophy, amino acid biosynthesis and oxidative responses appear to be involved in hypertrophic hepatocarcinogenesis. Early detection and toxicogenomic characterization of liver hypertrophy using our models may be useful for predicting carcinogenesis. In addition, the identified genes provide novel insight into discrimination between adverse hypertrophy associated with carcinogenesis and adaptive hypertrophy in risk assessment. - Highlights: • Hypertrophy (H) and hypertrophic carcinogenesis (C) were studied by toxicogenomics. • Important genes for H and C were selected by logistic ridge regression analysis. • Amino acid biosynthesis and oxidative responses may be involved in C. • Predictive models for H and C provided 94.8% and 82.7% accuracy, respectively. • The identified genes could be useful for assessment of liver hypertrophy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Reverse logistics system and recycling potential at a landfill: A case study from Kampala City

Highlights: • Quantifies the different waste streams delivered at the landfill. • Evaluates the amount of potential waste products that enters into the reverse cycle. • Drawing out the reverse logistics activities from Kampala City to Kiteezi landfill. • Identify the storage, collection and transportation mechanisms of products to the various destinations; and finally. • The study suggests efficient measures to improve reverse logistics system. - Abstract: The rapid growing population and high urbanisation rates in Sub-Saharan Africa has caused enormous pressure on collection services of the generated waste in the urban areas. This has put a burden on landfilling, which is the major waste disposal method. Waste reduction, re-use and recycling opportunities exist but are not fully utilized. The common items that are re-used and re-cycled are plastics, paper, aluminum, glass, steel, cardboard, and yard waste. This paper develops an overview of reverse logistics at Kiteezi landfill, the only officially recognised waste disposal facility for Kampala City. The paper analyses, in details the collection, re-processing, re-distribution and final markets of these products into a reversed supply chain network. Only 14% of the products at Kiteezi landfill are channeled into the reverse chain while 63% could be included in the distribution chain but are left out and disposed of while the remaining 23% is buried. This is because of the low processing power available, lack of market value, lack of knowledge and limited value addition activities to the products. This paper proposes possible strategies of efficient and effective reverse logistics development, applicable to Kampala City and other similar cities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Improving logistic efficiency of WEEE collection through dynamic scheduling using simulation modeling

Highlights: • Latest EU regulation on WEEE require more flexible logistics models. • The implementation of dynamic scheduling is evaluated for WEEE collection. • A hybrid simulation model compares dynamic (pure and “mixed”) and static collection schemes. • Results confirm the higher flexibility and efficiency of dynamic systems. • Dynamic scheduling “mixed” solutions result more efficient than pure ones. - Abstract: The complexity of collection systems for Waste from Electric and Electronic Equipment (WEEE) in the EU is increasing, due to the latest directive that sets new collection targets and modes. The high variability and the uncertainty of reverse flows require innovative logistic approaches. One recent option for increasing efficiency and responsiveness in waste collection services, boosted by new technological solutions for waste level monitoring, is to adopt a dynamic collection scheme, where the collection frequency is not established a priori (based on a fixed plan), but it is based on the actual filling levels of waste bins. This option can allow the service provider to plan the collection service following the actual demand, resulting in a more responsive service, while improving the logistic efficiency. This paper evaluates the implementation of dynamic scheduling schemes for the collection of WEEE. A hybrid simulation model has been developed in order to support researchers and practitioners in assessing quantitative impacts of adopting dynamic scheduling in WEEE collection. Three logistic alternatives (a fixed collection schedule scheme, a pure dynamic scheme and a mixed one) have been compared in a test case based on data of an Italian municipality; collection services for different types of WEEE (i.e. large appliances and small items) have been analyzed. Results show a promising performance of dynamic schedules compared to the fixed one, revealing, for the specific test case, how a mixed solution can combine the advantages of dynamic and fixed scheduling, gaining flexibility towards customer demand while improving truck resource utilization.

42 ENGINEERING↗

DOE OSTI2015

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

A Provably Accurate Randomized Sampling Algorithm for Logistic Regression

In statistics and machine learning, logistic regression is a widely-used supervised learning technique primarily employed for binary classification tasks. When the number of observations greatly exceeds the number of predictor variables, we present a simple, randomized sampling-based algorithm for logistic regression problem that guarantees high-quality approximations to both the estimated probabilities and the overall discrepancy of the model. Our analysis builds upon two simple structural conditions that boil down to randomized matrix multiplication, a fundamental and well-understood primitive of randomized numerical linear algebra. We analyze the properties of estimated probabilities of logistic regression when leverage scores are used to sample observations, and prove that accurate approximations can be achieved with a sample whose size is much smaller than the total number of observations. To further validate our theoretical findings, we conduct comprehensive empirical evaluations. Overall, our work sheds light on the potential of using randomized sampling approaches to efficiently approximate the estimated probabilities in logistic regression, offering a practical and computationally efficient solution for large-scale datasets.

Chowdhury, Agniva↗

DOE OSTI2014

Uncertainties in Life Cycle Greenhouse Gas Emissions from Advanced Biomass Feedstock Logistics Supply Chains in Kansas

To meet Energy Independence and Security Act (EISA) cellulosic biofuel mandates, the United States will require an annual domestic supply of about 242 million Mg of biomass by 2022. To improve the feedstock logistics of lignocellulosic biofuels and access available biomass resources from areas with varying yields, commodity systems have been proposed and designed to deliver on-spec biomass feedstocks at preprocessing “depots”, which densify and stabilize the biomass prior to long-distance transport and delivery to centralized biorefineries. The harvesting, preprocessing, and logistics (HPL) of biomass commodity supply chains thus could introduce spatially variable environmental impacts into the biofuel life cycle due to needing to harvest, move, and preprocess biomass from multiple distances that have variable spatial density. This study examines the uncertainty in greenhouse gas (GHG) emissions of corn stover logisticsHPL within a bio-ethanol supply chain in the state of Kansas, where sustainable biomass supply varies spatially. Two scenarios were evaluated each having a different number of depots of varying capacity and location within Kansas relative to a central commodity-receiving biorefinery to test GHG emissions uncertainty. Monte Carlo simulation was used to estimate the spatial uncertainty in the HPL gate-to-gate sequence. The results show that the transport of densified biomass introduces the highest variability and contribution to the carbon footprint of the logistics HPL supply chain (0.2-13 g CO 2 e/MJ). Moreover, depending upon the biomass availability and its spatial density and surrounding transportation infrastructure (road and rail), logistics HPL processes can increase the variability in life cycle environmental impacts for lignocellulosic biofuels. Within Kansas, life cycle GHG emissions could range from 24 to 41 g CO 2 e/MJ depending upon the location, size and number of preprocessing depots constructed. However, this range can be minimized through optimizing the siting of preprocessing depots where ample rail infrastructure exists to supply biomass commodity to a regional biorefinery supply system

09 BIOMASS FUELS↗

NASA NTRS1990

Expendable launch vehicles in Space Station Freedom logistics resupply operations

The projected Space Station Freedom (SSF) annual logistics resupply requirements were predicted to exceed the 1988 baseline Shuttle resupply system capability. This paper examines the implications of employing a 'mixed fleet' of Shuttles and ELVs to provide postassembly, steady-state logistics resupply. The study concluded that ELVs supported by the OMV could provide the additional required resupply capability with one to three launches per annum. However, the study determined that such a capability would require significant programmatic commitments, including baseline SSF OMV accommodations, on-orbit OMV monoprop replenishment capability, and substantial economics investments. The study also found the need for a half-size pressurized logistics module for the increase in the efficiency of logistics manifesting on the Shuttle as well as ELVs.

Newman, J. Steven↗

NASA NTRS1990

Space Station logistics policy - Risk management from the top down

Considerations are presented in the area of risk management specifically relating to logistics and system supportability. These considerations form a basis for confident application of concurrent engineering principles to a development program, aiming at simultaneous consideration of support and logistics requirements within the engineering process as the system concept and designs develop. It is shown that, by applying such a process, the chances of minimizing program logistics and supportability risk in the long term can be improved. The problem of analyzing and minimizing integrated logistics risk for the Space Station Freedom Program is discussed.

Paules, Granville↗

NASA NTRS2009

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Duda, David P.↗

NASA NTRS2010

Developing a Logistics Data Process for Support Equipment for NASA Ground Operations

The United States NASA Space Shuttle has long been considered an extremely capable yet relatively expensive rocket. A great part of the roughly US $500 million per launch expense was the support footprint: refurbishment and maintenance of the space shuttle system, together with the long list of resources required to support it, including personnel, tools, facilities, transport and support equipment. NASA determined to make its next rocket system with a smaller logistics footprint, and thereby more cost-effective and quicker turnaround. The logical solution was to adopt a standard Logistics Support Analysis (LSA) process based on GEIA-STD-0007 http://www.logisticsengineers.org/may09pres/GEIASTD0007DEXShortIntro.pdf which is the successor of MIL-STD-1388-2B widely used by U.S., NATO, and other world military services and industries. This approach is unprecedented at NASA: it is the first time a major program of programs, Project Constellation, is factoring logistics and supportability into design at many levels. This paper will focus on one of those levels NASA ground support equipment for the next generation of NASA rockets and on building a Logistics Support Analysis Record (LSAR) for developing and documenting a support solution and inventory of resources for. This LSAR is actually a standards-based database, containing analyses of the time and tools, personnel, facilities and support equipment required to assemble and integrate the stages and umbilicals of a rocket. This paper will cover building this database from scratch: including creating and importing a hierarchical bill of materials (BOM) from legacy data; identifying line-replaceable units (LRUs) of a given piece of equipment; analyzing reliability and maintainability of said LRUs; and therefore making an assessment back to design whether the support solution for a piece of equipment is too much work, i.e., too resource-intensive. If one must replace or inspect an LRU too much, perhaps a modification of the design of the equipment can make such operational effort unnecessary. Finally, this paper addresses processes of tying resources to a timeline of tasks performed in ground operations: this enables various overarching analyses, e.g., a summarization of all resources used for a given piece of equipment. Quality Control of data will also be discussed: importing and exporting data from product teams, including spreadsheets-todatabase or data exchange between databases.

Chakrabarti, Suman↗

NASA NTRS2012

Mission Benefits Analysis of Logistics Reduction Technologies

Future space exploration missions will need to use less logistical supplies if humans are to live for longer periods away from our home planet. Anything that can be done to reduce initial mass and volume of supplies or reuse or recycle items that have been launched will be very valuable. Reuse and recycling also reduce the trash burden and associated nuisances, such as smell, but require good systems engineering and operations integration to reap the greatest benefits. A systems analysis was conducted to quantify the mass and volume savings of four different technologies currently under development by NASA fs Advanced Exploration Systems (AES) Logistics Reduction and Repurposing project. Advanced clothing systems lead to savings by direct mass reduction and increased wear duration. Reuse of logistical items, such as packaging, for a second purpose allows fewer items to be launched. A device known as a heat melt compactor drastically reduces the volume of trash, recovers water and produces a stable tile that can be used instead of launching additional radiation protection. The fourth technology, called trash ]to ]supply ]gas, can benefit a mission by supplying fuel such as methane to the propulsion system. This systems engineering work will help improve logistics planning and overall mission architectures by determining the most effective use, and reuse, of all resources.

Ewert, Michael K.↗

NASA NTRS2013

Mission Benefits Analysis of Logistics Reduction Technologies

Future space exploration missions will need to use less logistical supplies if humans are to live for longer periods away from our home planet. Anything that can be done to reduce initial mass and volume of supplies or reuse or recycle items that have been launched will be very valuable. Reuse and recycling also reduce the trash burden and associated nuisances, such as smell, but require good systems engineering and operations integration to reap the greatest benefits. A systems analysis was conducted to quantify the mass and volume savings of four different technologies currently under development by NASA s Advanced Exploration Systems (AES) Logistics Reduction and Repurposing project. Advanced clothing systems lead to savings by direct mass reduction and increased wear duration. Reuse of logistical items, such as packaging, for a second purpose allows fewer items to be launched. A device known as a heat melt compactor drastically reduces the volume of trash, recovers water and produces a stable tile that can be used instead of launching additional radiation protection. The fourth technology, called trash-to-gas, can benefit a mission by supplying fuel such as methane to the propulsion system. This systems engineering work will help improve logistics planning and overall mission architectures by determining the most effective use, and reuse, of all resources.

Ewert, Michael K.↗

NASA NTRS2016

Multipurpose Cargo Transfer Bags fro Reducing Exploration Mission Logistics

The Logistics Reduction (LR) project within the Advanced Exploration Systems (AES) division is tasked with reducing logistical mass and repurposing logistical items. Multipurpose Cargo Transfer Bags (MCTB) have been designed such that they can serve the same purpose as a Cargo Transfer Bag (CTB), the common logistics carrying bag for the International Space Station (ISS). After use as a cargo carrier, a regular CTB becomes trash, whereas the MCTB can be unfolded into a flat panel for reuse. Concepts and potential benefits for various MCTB applications will be discussed including partitions, crew quarters, solar radiation storm shelters, acoustic blankets, and forward osmosis water processing. Acoustic MCTBs are currently in use on ISS to reduce the noise generated by the T2 treadmill, which reaches the hazard limit at high speeds. The development of the AMCTB included identification of keep out zones, acoustic properties, deployment considerations, and structural testing. Features developed for these considerations are applicable to MCTBs for all crew outfitting applications.

Baccus, Shelley↗