<?xml version="1.0" encoding="UTF-8"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-10-19T00:27:50Z</responseDate><request verb="GetRecord" identifier="oai:ebyu-rdlopen.rawdatalibrary.net:ebyu/10183" metadataPrefix="oai_dc">https://ebyu-rdlopen.rawdatalibrary.net/oai/request</request><GetRecord><record><header><identifier>oai:ebyu-rdlopen.rawdatalibrary.net:ebyu/10183</identifier><datestamp>2026-10-18T20:34:01Z</datestamp><setSpec>openaire</setSpec><setSpec>driver</setSpec><setSpec>com_ebyu_10000</setSpec><setSpec>col_ebyu_10001</setSpec></header><metadata><oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:title>Model-Based Exergy and Partial Techno-Economic Screening of Hydrogen, Ammonia, E-Diesel, and Waste Cooking Oil Biodiesel Pathways for Heavy-Duty Internal Combustion Engines</dc:title><dc:creator>Demirci, Oğuz Kürşat</dc:creator><dc:subject>ammonia</dc:subject><dc:subject>e-diesel</dc:subject><dc:subject>heavy-duty engine</dc:subject><dc:subject>hydrogen</dc:subject><dc:subject>Latin hypercube sampling</dc:subject><dc:subject>partial techno-economic screening</dc:subject><dc:subject>reduced-order exergy model</dc:subject><dc:subject>reproducibility</dc:subject><dc:subject>VECTO</dc:subject><dc:subject>waste cooking oil biodiesel</dc:subject><dc:subject>Brakes</dc:subject><dc:subject>Cost reduction</dc:subject><dc:subject>Diesel engines</dc:subject><dc:subject>Economic analysis</dc:subject><dc:subject>Exergy</dc:subject><dc:subject>Fleet operations</dc:subject><dc:subject>Hydrogen fuels</dc:subject><dc:subject>Taxation</dc:subject><dc:subject>Waste incineration</dc:subject><dc:subject>Calculation tools</dc:subject><dc:subject>Consumption calculation</dc:subject><dc:subject>Exergy modeling</dc:subject><dc:subject>Heavy duty engines</dc:subject><dc:subject>Reduced order</dc:subject><dc:subject>Reproducibilities</dc:subject><dc:subject>Techno-economics</dc:subject><dc:subject>Vehicle energy consumption</dc:subject><dc:subject>Vehicle energy consumption calculation tool</dc:subject><dc:subject>Waste cooking oil</dc:subject><dc:description>Five pathways—diesel, renewable hydrogen, green ammonia, Fischer–Tropsch e-diesel, and B100 waste cooking oil fatty acid methyl ester (WCO-FAME)—were compared on a common service basis using a reduced-order engine exergy model, a partial techno-economic cost model, and 10,000 Latin hypercube simulation samples; each alternative was paired with diesel by sample index. The results were normalised to 1 kWh of net brake work (kWhb) and 1000 tonne-kilometres of freight work (1000 tkm). A carbon balance back-calculation from European Commission Vehicle Energy Consumption Calculation Tool (VECTO) monitoring data for subgroup 5-Long Haul (5-LH; a 4 × 2 tractor–semitrailer) yielded 89.31 kWhb/1000 tkm; first-order payload penalties increased this requirement to 94.79 kWhb/1000 tkm for hydrogen and 91.97 kWhb/1000 tkm for ammonia. Deterministic central-case exergy efficiencies were 43.02% for hydrogen, 39.67% for e-diesel, 39.35% for diesel, 37.56% for B100, and 33.81% for ammonia. The study-specific partial cost was expressed in 2025 EUR per 1000 tkm and included delivered fuel, maintenance, and annualised incremental vehicle capital; common fleet costs, including driver, tyre, toll, insurance, and tax costs, and externalities were excluded. Therefore, this metric was not a full freight cost or tariff. Deterministic central-case costs were EUR 25.85/1000 tkm for diesel, EUR 26.72/1000 tkm for B100, EUR 58.64/1000 tkm for hydrogen, EUR 59.84/1000 tkm for ammonia, and EUR 67.44/1000 tkm for e-diesel. Hydrogen exceeded diesel in exergy efficiency in 96.50% of the paired simulation samples; all three electrofuel pathways were costlier than diesel in every paired simulation sample, whereas B100 was cheaper than diesel in 35.62% of the paired simulation samples. Thus, hydrogen led in exergy efficiency, diesel in cost under the defined partial economic boundary, and B100 was the closest cost competitor. These are conditional model-screening results rather than a completed comparative life-cycle assessment: no quantitative life-cycle impact assessment (LCIA), environmental ranking or marginal abatement cost result is reported. © 2026 by the author.</dc:description><dc:publisher>Multidisciplinary Digital Publishing Institute (MDPI)</dc:publisher><dc:date>2026</dc:date><dc:type>Article</dc:type><dc:identifier>https://rdlopen.rawdatalibrary.net/r/ebyu/10183</dc:identifier><dc:identifier>https://doi.org/10.3390/pr14172764</dc:identifier><dc:identifier>2227-9717</dc:identifier><dc:language>en</dc:language><dc:relation>Processes</dc:relation><dc:rights>info:eu-repo/semantics/openAccess</dc:rights><dc:type>info:eu-repo/semantics/article</dc:type><dc:identifier>https://ebyu-rdlopen.rawdatalibrary.net/tr/items/ebyu/10183</dc:identifier></oai_dc:dc></metadata></record></GetRecord></OAI-PMH>