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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 OSTI2023

A Machine Learning–Based Tire Life Prediction Framework for Increasing Life of Commercial Vehicle Tires

In the commercial freight industry, tire retreading decisions are often conservative due to limited knowledge of a tire’s remaining service life. This practice leads to increased costs and material waste. This paper proposes a machine learning–based approach for estimating tire casing life and retreadability, focusing on usage data rather than wear information. This approach could extend the tire’s lifespan and reduce landfill waste. Data integration from diverse tire casing measurement sources presents challenges, including imbalanced removal data. Our methodology addresses these challenges by using historical inspection, telematics, and finite element modeling (FEM) datasets. We introduce “Tire Casing Energy” as a comprehensive usage input and apply a Variance-Reduction Synthetic Minority Oversampling Technique (VR-SMOTE) for data imbalance rectification. A random forest model is used to estimate the state of the tire casing and the casing removal probability, with Bayesian optimization applied for hyperparameter tuning, enhancing model accuracy. Here, the proposed prediction framework is able to differentiate different truck fleets and tire locations based on their usage parameters. With the aid of this machine learning model, the importance and sensitivity of different tire usage parameters can be obtained, which is beneficial to maximize tire life.

Data balancing↗
DOE OSTI2020

3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles

The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Phase I DOE DE-SC0021823 Entitled “Changing the Design Rules of Rubber to Create Lighter Weight, More Fuel Efficient Tires” Final Technical Report 04/08/2022

Molecular Rebar Design, LLC has successfully developed new rubber composites with individualized carbon nanotubes called MOLECULAR REBAR® (MR), improving tire tread compound performance for use with electric vehicles (EVs). Through the iterative nature of the Phase I experimentation, MRD developed a novel carbon nanotube material that disperses well with other typical tire compound fillers and can be chemically functionalized for unique material property benefits. The new MR material is a chemically functionalized, discrete multi-wall carbon nanotube that binds into the rubber compound using silane technology. This Molecular Rebar based tire tread material drastically improves DIN abrasion resistance 25%+ (correlating to improved tire life), reduces tread weight by 6-7%, and reduces rolling resistance 20%+ (correlating to improved energy efficiency), as compared to an in-use, state-of-the-art, silica-silane tread compound. The formulations can be adjusted to maximize energy efficiency, to maximize wear or to have a blend of improvement depending on the tire performance needs of end use customers.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring

We introduce a novel digital twin (DT) framework for the predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the DT framework can be used to enhance automotive safety and efficiency, and how the technical challenges can be overcome using a three-step approach. First, to manage the data complexity over a long operation span, we employ data reduction techniques to concisely represent physical tires using historical performance and usage data. Relying on these data, for fast real-time prediction, we train a transformer-based model offline on our concise dataset to predict future tire health over time, represented as remaining casing potential (RCP). Based on our architecture, our model quantifies both epistemic and aleatoric uncertainties, providing reliable confidence intervals around predicted RCP. Second, to incorporate real-time data, we update the predictive model in the DT framework, ensuring its accuracy throughout its lifespan with the aid of hybrid modeling and the use of the discrepancy function. Third, to assist decision-making in predictive maintenance, we implement a tire state decision algorithm, which strategically determines the optimal timing for tire replacement based on RCP forecasted by our transformer model. This approach ensures that our DT accurately predicts system health, continually refines its digital representation, and supports predictive maintenance decisions. Furthermore, our framework effectively embodies a physical system, leveraging big data and machine learning (ML) for predictive maintenance, model updates, and decision-making.

advanced computing infrastructure↗
DOE OSTI2025

Sustainable Tire Production: Catalytic Upgrading of Ethanol into Butadiene (CRADA 636) Abstract

Bridgestone aims to minimize resource depletion and greenhouse gas (GHG) emissions by using 100% sustainable materials by 2050. As part of this goal Bridgestone is working to develop a first-of-kind end-of-life recycling process for tire material circularity and the decarbonization of new tire production. Used tires can be gasified to produce intermediate syngas (H 2 + CO) that can be further converted into ethanol using mature technology. The ethanol can then be converted into butadiene, a key precursor of new tires, using patented PNNL technology, enabling circularity for end-of-life tires. Indeed, PNNL has developed a new patented thermocatalytic-based technology for the conversion of ethanol into butadiene that allows for high carbon efficiency and improved catalyst longevity compared to World War II baseline catalyst. The objective here is to continue the development of this processing with the goal of commercial deployment. This includes development of engineered catalysts (e.g., extrudates) and their evaluation under industrially relevant conditions for deployment of a pilot scale. If successful, Bridgestone will subsequently utilize this catalyst technology at pilot and then commercialization scale creating jobs in both construction sector and industry sector in a chosen location that promotes greater diversity, equity, and inclusion through key policies, training, and recruiting practices. Taken together, this work will support the U.S. Department of Energy goal for production of renewable chemicals with > 70% GHG emissions reduction relative to petroleum-derived counterparts and supporting > 1 MMT/ yr CO 2 e emissions reduction by 2030.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sustainable valorization of waste tires: Selective hydrotreating for renewable p-cymene production

The escalating global concern over waste tire management driven by the surge in automobiles necessitates sustainable and innovative solutions. Here, this study posits a novel approach by introducing a selective catalytic hydrogenation and dehydrogenation process using a tandem two-stage pressurized fixed-bed reactor, aiming to convert waste tires into valuable sulfur-free p-cymene. The experimental results indicate that among the studied catalysts including Pt/C, Pd/C, Ru/C, and Ni/Al 2 O 3 -SiO 2 , the Pd/C exhibits concomitant hydrogenation and dehydrogenation functionalities, achieving full conversion and displaying 100 % selectivity towards p-cymene from limonene model compound. Furthermore, the Pd/C catalyst demonstrates remarkable efficiency in converting real-world waste tires into p-cymene, yielding up to 134.8 mg/g at optimal conditions. Importantly, this catalyst also facilitates complete hydrodesulfurization activity, addressing environmental concerns by producing sulfur-free liquid products. This innovative method not only optimizes p-cymene synthesis from waste tires but also contributes to environmental sustainability, showcasing both economic and ecological viability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Demineralization of Carbon Black Derived from End-of-Life Tires

The research carried out in this exploratory research demonstrates an energy and cost-efficient method to purify carbon black recovered from waste tires for recycling back into tires or rubber products. Compared to conventional methods, the methods explored demonstrate improvements in product purity by 40%-60%, a reduction in water requirements by 50%, reduction in processing costs by 80%-90%, and processing/embodied energy by 70%-95%. A techno-economic feasibility analysis of a pilot scale operation shows that these new demineralization methods explored in this work are potentially economically viable. Further development and implication of this technology would help enable cleanup of waste tires and recycling of tires. The work carried out in this study has been successful in demonstrating a new processing method to produce recycled carbon black (rCB) with drastically improved economic viability and impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Apparatus and method for manufacturing an air maintenance tire

Apparatus and method for manufacturing an air maintenance tire includes an air pumping tube assembly station constructing an air pumping tube sub-assembly, a tire preparation station for forming passageways in the tire to accept an outlet device of the air pumping tube sub-assembly, an air pumping tube sub-assembly installation station and a pressure regulator installation station. The air pumping tube sub-assembly inserts into an elongate tire groove opening, facilitated by groove-spreading apparatus.

42 ENGINEERING↗
DOE OSTI2020

Apparatus and method for assembling a pumping tube into an air maintenance tire sidewall groove

Apparatus and method of assembling an elongate air pumping tube into an elongate tire sidewall groove includes engaging the tire sidewall outward surface with an impact wheel at an impact location proximally adjacent and above the elongate groove as the tire is rotated. The groove is thereby spread segment-by-segment for segment-by-segment synchronous insertion of the tube into the groove. The groove is closed segment-by-segment as each spread segment is returned to its original narrower dimension utilizing elastomeric material composition properties of the tire sidewall.

42 ENGINEERING↗
DOE OSTI2026

Urban wash-off of tire wear particles

Tire wear particles (TWPs) are an important class of microplastics due to their toxicity and abundance. Because most TWPs are generated on impervious road surfaces, urban wash-off is the critical first phase of waterborne transport from their zone of production to stormwater drainage. However, little is known about the driving factors behind their mobilization. In this study, we use a rainfall simulator to investigate how surface roughness, rainfall intensity, and surface slope affect wash-off behaviors of TWPs. We also analyze how the size and shape of mobilized TWPs change over the course of simulated storm events. We found that low surface roughness, high rainfall intensity (most significant factor), and low slope result in the most rapid conveyance of TWP load. On average, large particles (>1000 µm) travelled faster than small particles (<125 µm). Particle shape explained a very small amount of variance in TWP wash-off velocity but was found to be more important under higher surface roughness conditions. In addition to wash-off velocity, we found similar conditions controlled the percent mobilization of TWPs. Low surface roughness and high rainfall intensity resulting in higher TWP wash-off rates is consistent with mineral sediment wash-off behavior. Conversely, low surface slope and large particle size leading to faster conveyance is directly opposed to mineral sediment wash-off. Our findings suggest drag-dominated flow and that sufficient runoff depth is the most important parameter governing TWP wash-off. These findings are important first steps to understanding wash-off behaviors of TWPs and informing future modeling efforts and mitigation strategies.

13 HYDRO ENERGY↗
DOE OSTI2020

Materials Data on TiRe by Materials Project

TiRe is Tetraauricupride structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Ti is bonded in a body-centered cubic geometry to eight equivalent Re atoms. All Ti–Re bond lengths are 2.70 Å. Re is bonded in a body-centered cubic geometry to eight equivalent Ti atoms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Advanced Non-Tread Materials for Fuel-Efficient Tires

PPG Industries, Inc. proposes to develop a new silica filler that can increase fuel efficiency by 2% while maximizing key performance properties in non-tread tire components compared to current carbon black/silica filler blends. In this project PPG focused on a sidewall compound. The developed compounds/components will reduce energy losses by approximately 25%, with no more than a 5% loss of resistance to degradative forces (targeting better performance). PPG plans to achieve this goal by characterizing the impact the silica filler can have on rubber properties and then tuning the silica morphology and surface chemistry for this end use. PPG will also provide guidance in optimizing the compound formulation to make the best use of this new filler. A key aspect is to understand and maintain, if not improve, the aging performance as evaluated by crack growth resistance under ozone environment. Two key strategies were used to meet the rolling resistance goal while maintaining other performance properties. The first factor was understanding the surface treatments and chemical makeup of the silica and its effects on compound performance. The second factor was using the best performing silicas and determining the optimum compound modifications to achieve the final sidewall compound performance. Using statistical analysis throughout the optimization process, it was determined that changing the silica morphology played a role in improving the reduction of tear strength while reducing rolling resistance and the improvements observed varied depending on the CB type.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Study of Electric Vehicle Range Loss Associated with Replacement Tires

The FuelEconomy.Gov website has become a trusted source for consumers to find information pertaining to fuel economy and fuel-efficient vehicles. As electric vehicles are an increasingly important part of the light-duty fleet in the U.S., there is a need to expand the website content that is targeted to electric vehicle (EV) owners. This report addresses a concern about which several anecdotal reports have come to the attention of the website support staff. Specifically, some EV owners have observed a sudden, noticeable decrease in their all-electric range when they replace the tires that came with their vehicle when it was new. This change has reportedly led some owners to take their vehicles to the dealership service department out of concern that something had gone wrong with the vehicle.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm

Market uncertainties motivate the development of flexible polygeneration systems that are able to adjust operating conditions to favor production of the most profitable product portfolio. However, this operational flexibility comes at the cost of higher capital expenditure. A scenario-based two-stage stochastic nonconvex Mixed-Integer Nonlinear Programming (MINLP) approach lends itself naturally to optimizing these trade-offs. This work studies the optimal design and operation under uncertainty of a hybrid feedstock flexible polygeneration system producing electricity, methanol, dimethyl ether, olefins or liquefied (synthetic) natural gas. A recently developed C++ based software framework (named GOSSIP) is used for modeling the optimization problem as well as its efficient solution using the Nonconvex Generalized Benders Decomposition (NGBD) algorithm. Two different cases are studied: The first uses estimates of the means and variances of the uncertain parameters from historical data, whereas the second assesses the impact of increased uncertain parameter volatility. The value of implementing flexible designs characterized by the value of the stochastic solution (VSS) is in the range of 260–405 M$ for a scale of approximately 893 MW of thermal input. Increased price volatility around the same mean results in higher expected net present value and VSS as operational flexibility allows for asymmetric exploitation of price peaks.

42 ENGINEERING↗