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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Sensorless Estimation of In-Cabin CO2 Concentration for Model-Based Air Recirculation Control</title>
      <link>https://trid.trb.org/View/2691886</link>
      <description><![CDATA[This paper introduces a sensorless approach for data-driven modeling of in-cabin CO2 concentration to optimize air recirculation flap control without the need for a dedicated CO2 sensor. Elevated CO2 concentrations, resulting from passenger exhalation, can impair occupants’ cognitive function and comfort. Current state-of-the-art solutions rely either on time-based control strategies, which lack responsiveness to actual cabin conditions, or on direct CO2 measurements via sensors, which increase system complexity and costs. In contrast, the proposed approach aims to replicate the benefits of sensor-based control without requiring physical sensors. In this study, a model-based methodology is presented, utilizing empirical CO2 measurement data collected from real-world test drives at varying occupancies, fan stages, vehicle speeds, and flap positions. Data acquisition involves a multi-gas analyzer positioned within the passengers’ breathing zone under controlled operation of the vehicle’s climate control unit. Based on these measurements, time-dependent CO2 concentration profiles are represented using exponential functions. These regression curves capture CO2 accumulation, depletion, and balancing behaviors, considering factors such as cabin leakage, pressure differentials at varying speeds, and ventilation conditions. These influences are inherently included in the calibration curves due to their empirical basis. The derived regression curves are implemented into a control model to simulate CO2 concentration throughout the drive, including situations where outside pollution is high and prolonged air recirculation is necessary – such as when driving through tunnels or behind trucks. On the baseline of this simulation, the sensorless control strategy adjusts flap positions accordingly, thereby minimizing both excessive CO2 buildup and unnecessary energy losses due to overventilation. By omitting CO2 sensors and relying solely on existing in-vehicle databus signals, this approach offers a cost-effective solution for cabin air quality management. Future work will focus on real-world validation of the control model and integration of exterior air quality monitoring as a complementary input.]]></description>
      <pubDate>Wed, 03 Jun 2026 09:07:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691886</guid>
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    <item>
      <title>The state of modelling for evaluating health equity impacts of freight emissions</title>
      <link>https://trid.trb.org/View/2673074</link>
      <description><![CDATA[Evaluating health equity impacts of freight emissions is crucial for developing a sustainable and just freight system. It is a complex process that requires interdisciplinary knowledge, including transportation, environment, and public health. Full-chain simulation is an important approach for forecasting freight planning outcomes. However, a systematic framework that integrates available models in full-chain and is specifically designed for the freight sector has not been developed. We review 36 empirical studies covering this interdisciplinary topic, and summarise the commonly used models. We find that EMission FACtor (EMFAC) and Motor Vehicle Emission Simulator (MOVES) models are commonly used to estimate freight vehicle emissions, with their outputs serving as inputs for air quality models, such as Community Multiscale Air Quality Model (CMAQ) or Intervention model for air pollution (InMAP). To estimate the health effects, concentration-response (C-R) functions, combined with static or dynamic demographic and socioeconomic data, are used to quantify the relationship between changes in pollutant concentrations and health outcomes. Then, disparity analysis relies on the assumption of age-specific C-R functions and examines statistical differences between demographic groups – including racial/ethnic groups, income levels, age groups, and other vulnerable communities. This study comprehensively outlines this state-of-the-art, integrated framework identified through the synthesis of this interdisciplinary literature. This framework can support future researchers in this field and policymakers.]]></description>
      <pubDate>Tue, 10 Mar 2026 09:54:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673074</guid>
    </item>
    <item>
      <title>Dimensionless Theory–Particle Swarm Optimization Prediction Framework for Diffusion Concentration Distribution of Buried Gas Pipeline Leakage</title>
      <link>https://trid.trb.org/View/2582016</link>
      <description><![CDATA[Previous research has underscored the importance of predicting concentration distributions from leaks in buried gas pipelines. This study addresses the limitations of existing prediction methods in handling complex, multifactorial leakage scenarios by proposing a diffusion concentration prediction framework with fusion of dimensionless theory and particle swarm optimization for buried gas pipeline leakage. This hybrid framework integrates model-driven and data-driven techniques to enhance the accuracy of gas leakage concentration distribution prediction in buried pipelines. On this basis, the paper presents case studies for both high-pressure and medium- to low-pressure buried gas pipeline leakage scenarios. The algorithm’s effectiveness and accuracy are verified by comparison with experimental data for high-pressure gas leakage, numerical simulation data for medium- and low-pressure leakage, and the previous theoretical models. The leakage concentration distribution prediction model for buried gas pipelines proposed in this study provides a useful tool for leakage detection and prediction of buried gas pipelines.]]></description>
      <pubDate>Fri, 24 Oct 2025 16:53:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2582016</guid>
    </item>
    <item>
      <title>Leakage Characteristic Analysis and Hazard Level Classification of Gas Pipelines Considering Layered Soil Backfilling</title>
      <link>https://trid.trb.org/View/2547975</link>
      <description><![CDATA[Soil coverage is the essential difference between buried pipelines and above-ground pipelines. The soil environment affects the leakage and diffusion characteristics of gas. In this paper, the impact of various types of soil layering structures on the leakage and diffusion of natural gas in soil was studied by using numerical simulation. The horizontal hazard range (HHR), the vertical hazard range (VHR), and the surface hazard range (SHR) were defined, five levels of natural gas hazards were categorized, and the degree of accidental hazard under 15 conditions was analyzed by using the lower explosion limit of methane (5% vol.) as the hazardous boundary. The results showed that when the first layer of backfilled soil above the pipeline was clay, the other types and arrangement orders of layered soils had less of an effect on the diffusion of gas concentration. The three layers of soil were subject to greater clay resistance, reducing VHR and increasing HHR and SHR. After 3,600 s of leakage, the hazard level for sand, loam-sand, loam-clay-sand, clay-sand-loam, and clay-loam-sand all reached Level V. The research findings of this paper will provide a reference basis for the design of soil backfilling schemes in the construction of buried gas pipeline projects.]]></description>
      <pubDate>Wed, 24 Sep 2025 15:24:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2547975</guid>
    </item>
    <item>
      <title>Detailed Event Mean Concentrations for Transportation Facilities</title>
      <link>https://trid.trb.org/View/2569143</link>
      <description><![CDATA[The objective of this project is to develop Event Mean Concentrations (EMC) for roadways (pavement only) and roadside (greenspace) for transportation.]]></description>
      <pubDate>Tue, 24 Jun 2025 11:35:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2569143</guid>
    </item>
    <item>
      <title>Gas jet structure effects on fuel concentrations and flames in a hydrogen low-pressure direct-injection spark-ignition engine</title>
      <link>https://trid.trb.org/View/2552344</link>
      <description><![CDATA[This study aims to find the impact of the nozzle shape of a side-mounted, 3.5-MPa pintle injector on hydrogen concentration and flame development in a low-pressure direct-injection spark ignition (H2LPDI) engine. To this end, endoscopic high-speed imaging of gas jet laser shadowgraph and flames as well as spark-induced breakdown-spectroscopy (SIBS) method are applied to one of the inline four cylinders of H2LPDI engine. Two engines with endoscopic access are used: one motored engine for high-speed laser shadowgraph imaging of gas jet development and the other combustion engine for SIBS-based spark gap ? measurements and high-speed hydrogen flame imaging. The gas jet visualisation showed that a nozzle with a narrower jet spreading angle leads to more turbulent jet boundaries and the jet axis being directed more towards the piston. Due to higher axial momentum, the narrower spreading angle nozzle also caused enhanced jet penetration across the in-cylinder tumble flow. This jet development pattern resulted in locally leaner hydrogen mixtures near the centrally mounted spark plug at the time of ignition, evidenced by a higher difference between spark gap ? and global ?. As a result, the flame size was measured smaller at any fixed combustion stage. For both nozzle types, the injection timing was also varied between 150 and 120 °CA bTDC but there was no significant difference measured in spark gap ? and flame size compared to that associated with the nozzle type.]]></description>
      <pubDate>Tue, 17 Jun 2025 09:58:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2552344</guid>
    </item>
    <item>
      <title>Concentrations and origins of ultrafine particles at a major European harbor</title>
      <link>https://trid.trb.org/View/2518775</link>
      <description><![CDATA[The maritime transport sector poses significant air quality concerns, particularly in nearby cities. Ultrafine particles (UFP, diameter < 100 nm) are of particular concern due to their potential health impacts. This study measured particle number concentrations (PNC), size distributions (PNSD), and other pollutants including particulate matter (PM), nitrogen oxides (NOₓ), black carbon (BC), sulfur dioxide (SO₂) and ozone (O₃), organic markers and trace elements at a major European harbor and an urban background (UB) location. The average PNC at the harbor was 1.8-fold higher than at the UB, with particularly marked differences in the Aitken mode (2.4-fold higher). NOₓ levels were 10.5-fold higher at the harbor, and NO₂, NOₓ and BC concentrations were 2.0 to 2.9 times greater compared to the UB site. SO₂ concentrations were also 1.7-fold higher at the harbor. Two distinct types of PNC peaks were observed: daytime peaks with high Aitken mode particles likely linked to transit ship emissions, and late afternoon/nighttime peaks with higher nucleation mode particles likely linked to thermal power plant emissions, docked cruise ships, and vehicular traffic related to ferry boarding. Source apportionment of PNC-PNSD through Positive Matrix Factorization (PMF) identified four key contributors to PNC at the harbor: Regional recirculation (9 %, modes: 100 nm and 35 nm), Nucleation (30 %, mode: 18 nm), Coastal background (22 %, mode: 75 nm), and Ship transit (33 %, mode, 35 nm). Concentrations of Ti, V, Cr, Ni, Cu, Zn, As, Sb, Pb and Na in the quasi-UFP range were more than twice at the harbor compared to the UB. This study provides insights into UFP concentrations and their sources within a major touristic and commercial harbor, highlighting the complexity of identifying specific contributions from various UFP emission sources in large harbors.]]></description>
      <pubDate>Fri, 23 May 2025 15:34:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2518775</guid>
    </item>
    <item>
      <title>Aircraft Air Quality and Bleed Air Contamination Detection [supporting datasets]</title>
      <link>https://trid.trb.org/View/2543096</link>
      <description><![CDATA[The purpose of this project was to provide a data-driven process to identify sensing technology with good potential for detecting bleed air contamination from engine oil, hydraulic fluid, or deicing fluid. Reports from major aircraft cabin air studies were reviewed to identify the range of constituents that can be expected in cabin air, especially as they pertain to the aforementioned contaminants and their potential markers. One of the projects was the National Aeronautics and Space Administration Vehicle Integrated Propulsion Research (NASA-VIPR) project where controlled amounts of engine oil were injected into the engine compressor of a C-17 transport aircraft and the resulting contaminants in the bleed air measured. Three additional cabin air quality studies conducted on revenue flights were reviewed. These three studies provide data for a combined total of 249 flights on a variety of makes and models of aircraft. These studies provide adequate documentation of typical aircraft cabin air. Information from this review was used to identify potential markers of the bleed air contaminants. Additionally, collaboration was established with several technical committees from the Society of Automotive Engineers (SAE), American Society of Heating, Air- Conditioning and Refrigerating Engineers (ASHRAE), and American Society for Testing and Materials (ASTM) technical committees and with project personnel from the prior European Union Aviation Safety Administration (EASA)-funded cabin air study. There was extensive interaction with SAE E31b and a formal collaboration agreement was established between ASHRAE research project 1830-RP and Kansas State University. Two industry webinars where held to obtain industry input and participation in the industry working group that was formed. Key objectives of the project were to identify sensors and sensing technology with potential for detection of one or more of the three aforementioned bleed air contaminants and to develop a plan for test stand engine experiments to evaluate the sensors with controlled amounts of the three contaminants. Sensors and instruments were identified and a test plan was developed. The detailed plan describing contaminants, rates, and operating conditions is presented in Section 4.11 of this report and instruments recommended for testing are described in Section 5.2. Additionally, through the collaboration with ASHRAE 1830 and the support of the industry working group, many of the experiments identified in the test plan were completed.]]></description>
      <pubDate>Wed, 23 Apr 2025 14:47:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2543096</guid>
    </item>
    <item>
      <title>Complicated pollution characteristics (particulate matter, heavy metals, microplastics, VOCs) of spent lithium-ion battery recycling at an industrial level</title>
      <link>https://trid.trb.org/View/2529543</link>
      <description><![CDATA[The recycling of spent lithium-ion batteries has become a common concern of the whole society, with a large number of studies on recycling management and recycling technology, but there is relatively little study on the pollution release during the recycling process. Pollution will restrict the healthy development of the recycling industry, which makes relevant research very significant. This paper monitored and analyzed the battery recycling pretreatment process in a formal factory, and studied the pollution characteristics of particulate matter, heavy metals, and microplastics under different treatment stages. In addition, the release characteristics of VOCs during pyrolysis were also studied. When the green pretreatment process was used, PM₁₀ concentration in most processing units was below 100 μg/m³, indicating that the overall pollution prevention and control effect in the workshop is well-done. Particulate matter in workshop contained a large amount of metal components, mainly Fe, Cu, Co, Mn, Ni, etc. Microplastics were widely distributed in ground dust, and small-size microplastics are suspended in the air for a long time because of Brownian motion. Collecting ground dust and particulate matters is beneficial for controlling the emission of microplastics. During thermal treatment, Ethylene carbonate and dimethyl carbonate in the electrolyte would enter the atmosphere, and a large amount of short chain hydrocarbons released together, forming VOCs pollution. This study summarized distribution characteristics of different pollutants in a battery recycling factory. The basic pollution data provided are beneficial for improving the recycling technology of spent lithium-ion battery.]]></description>
      <pubDate>Wed, 09 Apr 2025 09:52:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2529543</guid>
    </item>
    <item>
      <title>An Observer-Based Controller of Anode Pressure and Nitrogen Concentration for Fuel Cell System</title>
      <link>https://trid.trb.org/View/2511618</link>
      <description><![CDATA[Maintaining an appropriate permeated nitrogen concentration and stable anode pressure is crucial for fuel cell performance. However, direct detection of nitrogen concentration encounters challenges due to measurement limitations, and an abrupt pressure drop occurs during purging. In this article, an extended Kalman filter (EKF) observer is devised based on the lumped model and utilized for the anode side to filter the pressure signal, estimate the nitrogen fraction, and calculate the purge flow. The filtered pressure is utilized as feedback for a linear active disturbance rejection controller (LADRC) to achieve precise anode inlet pressure control. The estimated purge flow serves as the variable feedforward (VF) to compensate pressure fluctuation during purging, triggered by the nitrogen fraction threshold. The analysis between the traditional feedforward proportional-integral controller and the LADRC-VF underscores the better performance of the latter, showcasing a substantial reduction in anode inlet pressure. Finally, the LADRC-VF is validated on a 60 kW fuel cell system, demonstrating an average pressure fluctuation maintained within ±2 kPa and a 13% decrease in root mean square error (RMSE). Meanwhile, the observer-based purge strategy proves advantageous over traditional fixed interval purging, showcasing efficiency in total purge time savings while ensuring a low nitrogen concentration under dynamic load conditions.]]></description>
      <pubDate>Fri, 04 Apr 2025 16:54:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2511618</guid>
    </item>
    <item>
      <title>A Theoretical Model for the Correlation of Smoke Number to Dry Particulate Concentration in Diesel Exhaust</title>
      <link>https://trid.trb.org/View/1783386</link>
      <description><![CDATA[A correlation between reflectance type smoke measurements and dry particulate concentrations in diesel exhaust is derived from first principles. The model has one free parameter; the mass-average diameter of the exhaust particulates. Data from the literature indicates that particulate diameters can vary depending upon the injection hardware, fuel properties, and combustion chamber design. Older engines typically have larger average particulate radii and run at higher smoke numbers. Using a simple linear relationship between smoke number and mass-averaged particulate diameter, a good match is obtained between the derived model and experimental data. As a further validation of the model, a technique is derived by which any correlation between smoke and particulate concentration can be validated with only a smoke meter, provided it has multiple draw capabilities. Using this novel technique, the correlation derived here is shown to be functionally correct.]]></description>
      <pubDate>Fri, 07 Mar 2025 15:04:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/1783386</guid>
    </item>
    <item>
      <title>Aircraft Air Quality and Bleed Air Contamination Detection: Phase 2, Volume 2 [supporting dataset]</title>
      <link>https://trid.trb.org/View/2516405</link>
      <description><![CDATA[The purpose of this project was to provide a data driven process to identify sensor technologies with the potential for detecting and identifying low levels of contaminants that may occasionally be present in aircraft engine bleed air supplies. Bleed air from a ground-based aircraft propulsion engine and an auxiliary power unit (APU) were used to supply air through an ozone/volatile organic compound (VOC) converter to the environmental control system on a Boeing 747, while injecting controlled amounts of fluid contaminants (i.e., aircraft engine oil, hydraulic fluid, and deicing fluid). Measurements of contaminants were performed at the ozone/VOC converter inlet and exit, and at the air conditioning pack exit. Ultrafine particles (UFP) were found to be a sensitive marker for engine oil contamination with measurements at all three locations showing similar, highly elevated UFP concentrations with a mean diameter near 40nm and smaller when the sample stream was cooled to near room temperature. In situ measurements showed that UFPs are generated by condensation and high UFP concentrations were not detected in uncooled bleed air. Oil contamination VOC levels were very low upstream of the ozone/VOC converter at bleed air temperatures up to 220˚C and increased at bleed temperatures of around 315˚C; however, oil contamination VOC levels remained at sub-ppmv levels. Fine particle concentrations also increased with oil contamination at lower bleed air temperatures, but not with temperatures around 315 ˚C. Secondary contaminants including pentanoic acid, heptanoic acid, acetic acid, formaldehyde, and acetaldehyde formed in the ozone/VOC converter as the oil aerosol oxidized. Consideration must be given to contaminant deposition within the bleed air system and sample lines as this deposition may lead to delayed responses and contaminant release during temperature transients. Of the sensor technologies assessed, spectrometers provided the best opportunity to detect and identify contaminants. Carbon monoxide (CO) measurements confirmed that CO is not generated in sufficient quantities to be of value as a marker for engine oil or hydraulic fluid contamination of bleed air. CO may be useful as a marker for ingestion of engine exhaust in some cases. However, carbon dioxide (CO2) is a much better marker for engine exhaust ingestion.]]></description>
      <pubDate>Fri, 07 Mar 2025 15:04:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2516405</guid>
    </item>
    <item>
      <title>Aircraft Air Quality and Bleed Air Contamination Detection; On-Wing Tests, Sensor Technologies, and Chemical Sampling (Phase 2, Volume 2)</title>
      <link>https://trid.trb.org/View/2508899</link>
      <description><![CDATA[The purpose of this project was to provide a data driven process to identify sensor technologies with the potential for detecting and identifying low levels of contaminants that may occasionally be present in aircraft engine bleed air supplies. Bleed air from a ground-based aircraft propulsion engine and an auxiliary power unit (APU) were used to supply air through an ozone/volatile organic compound (VOC) converter to the environmental control system on a Boeing 747, while injecting controlled amounts of fluid contaminants (i.e., aircraft engine oil, hydraulic fluid, and deicing fluid). Measurements of contaminants were performed at the ozone/VOC converter inlet and exit, and at the air conditioning pack exit. Ultrafine particles (UFP) were found to be a sensitive marker for engine oil contamination with measurements at all three locations showing similar, highly elevated UFP concentrations with a mean diameter near 40nm and smaller when the sample stream was cooled to near room temperature. In situ measurements showed that UFPs are generated by condensation and high UFP concentrations were not detected in uncooled bleed air. Oil contamination VOC levels were very low upstream of the ozone/VOC converter at bleed air temperatures up to 220˚C and increased at bleed temperatures of around 315˚C; however, oil contamination VOC levels remained at sub-ppmv levels. Fine particle concentrations also increased with oil contamination at lower bleed air temperatures, but not with temperatures around 315 ˚C. Secondary contaminants including pentanoic acid, heptanoic acid, acetic acid, formaldehyde, and acetaldehyde formed in the ozone/VOC converter as the oil aerosol oxidized. Consideration must be given to contaminant deposition within the bleed air system and sample lines as this deposition may lead to delayed responses and contaminant release during temperature transients. Of the sensor technologies assessed, spectrometers provided the best opportunity to detect and identify contaminants. Carbon monoxide (CO) measurements confirmed that CO is not generated in sufficient quantities to be of value as a marker for engine oil or hydraulic fluid contamination of bleed air. CO may be useful as a marker for ingestion of engine exhaust in some cases. However, carbon dioxide (CO2) is a much better marker for engine exhaust ingestion.]]></description>
      <pubDate>Mon, 24 Feb 2025 09:11:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2508899</guid>
    </item>
    <item>
      <title>Analyzing Pollutant Concentrations in Two Main Greek Urban Centers</title>
      <link>https://trid.trb.org/View/2407172</link>
      <description><![CDATA[The main aim of the paper is to analyze the temporal behavior of air pollutant concentrations in two different Greek urban areas, Piraeus and Volos. Results indicate that the daily mean concentrations of PM10 exceeded the EU standards in both cities on a significant number of days over the most recent calendar years. Further, the Theil-Sen estimations indicate that the overall trend for PM2.5 in Piraeus is negative and statistically significant over the analysis period, whereas the trend analysis for PM10 in Piraeus, as well as for both PM2.5 and PM10 in Volos reflects only modest decreases that lack statistical significance, suggesting that more effective control measures and policies are needed to tackle this global challenge. Other results show that in Piraeus, CO and NOₓ exhibit similar seasonal and daily variations, with the highest concentrations in winter and the lowest in summer, and also with the highest concentrations on Fridays and the lowest over weekend days. Particulate matter (PM10 and PM2.5) shows similar temporal behavior in both urban areas, also registering higher concentrations in winter months, suggesting that the main culprit might be the use of unsustainable energy sources for heating. On the other hand, the O₃ concentration in Piraeus is highest in the summer months, reflecting strong solar radiation.]]></description>
      <pubDate>Mon, 13 Jan 2025 11:12:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2407172</guid>
    </item>
    <item>
      <title>Simulation Methodology for Hydrogen Concentration and Dilution Strategy in a Hydrogen Fueled Internal Combustion Engine</title>
      <link>https://trid.trb.org/View/2474912</link>
      <description><![CDATA[Manufacturers of internal combustion engines are changing their focus to non-conventional fuels like hydrogen in response to the worrying global warming situation. When compared to conventional fuels like gasoline or diesel, the use of gaseous hydrogen fuel in an internal combustion engine powered by hydrogen can lessen the engine's negative environmental effects. But occasionally, hydrogen can leak from the high-pressure fuel injection system to the engine top cover and as blowby within the crankcase. Static zones may emerge because of these H₂ leaks. Potential explosion or fire can result when the H₂ concentration in these stagnation zones is more than 4% and triggers a minimum ignition energy of 0.02 mJ. A CFD simulation methodology incorporating multi-species model, piston, and crank motion to estimate the H₂ concentration within crankcase is developed. The simulation development phases has been presented in the paper. The blowby values are determined from the experimental measurement and used as the inputs. The dilution strategy by varying the number of vent ports, location, size for crankcase is examined using this simulation. The flow requirements at various speed also deduced. Further, for under hood and engine top cover, underhood analysis is carried out to ascertain the accumulation within the engine and its compartment. Fan ON and OFF scenario is studied, and results are discussed. H₂ICE blowby and H₂ % concentration at breather tube out is correlated with test for a baseline case. A good correlation matching the experimental trend is observed in the simulation. The study helped engine program to complete the optimization and design verification through simulation and get the best concept implemented.]]></description>
      <pubDate>Mon, 13 Jan 2025 10:24:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2474912</guid>
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