58622 research outputs found
Sort by
Improving the predictive capability of empirical heat transfer correlations for hydrogen internal combustion engines
Get PDFHydrogen internal combustion is widely considered a viable technology to achieve near-zero tailpipe CO2 and NOx emissions for difficult-to-electrify applications due to the maturity of ICE technology and production facilities. One-dimensional/zero-dimensional (0D) modeling is a valuable tool for engine development due to its relatively low computational requirements, but hydrogen combustion models still require further development. A large factor is gas-to-wall heat transfer, which is higher for hydrogen combustion due to higher flame temperatures and shorter quenching distance. For accurate prediction of in-cylinder temperatures, and therefore combustion rates and knock propensity, a well calibrated heat transfer model is essential. This paper evaluates existing heat transfer models against previously published experimental cylinder pressure and heat flux data from a Cooperative Fuel Research (CFR) engine with hydrogen Port Fuel Injection (PFI). A new heat transfer correlation is developed, utilizing a new fluid properties correlation to better represent the change in viscosity and conductivity with changing hydrogen concentration. Recent developments in 0D turbulence models improve the characteristic velocity calculation, which is augmented with a combustion term. This model is tested against a second dataset from the CFR engine with lambda from 1.0 to 4.0 and compression ratios of 9–13, showing improved performance versus previously published models. Whilst the new model provides more consistent results during combustion for variations in lambda and compression ratio, it requires improvement in its prediction of heat loss during expansion, and further validation at higher engine speeds and different engine configurations
Synergistic catalytic removal of NO<sub>x</sub> and chlorinated aromatics via atomically dispersed asymmetric Mn-O-Ce sites on montmorillonite
Get PDFThe synergistic catalytic removal of nitrogen oxides (NOx) and chlorinated volatile organic compounds (CVOC) is in significant demand from both ecological and economic perspectives. Breaking the trade-off between synergistic catalytic activity and selectivity is a big challenge. In this study, we developed a catalyst named MnCeOx/MMT-Ti, which features an atomically dispersed MnCeOx supported on montmorillonite. It exhibited superior performance from 260 to 330 °C, achieving over 80 % conversion of NOx and chlorobenzene (CB), as well as over 80 % selectivity for N2 and CO2. Atomically dispersed asymmetric Mn-O-Ce sites were constructed and evidenced. The isolated asymmetric Mn-O-Ce sites in MnCeOx/MMT-Ti stimulated exceptional O2 adsorption and activation, facilitating CB oxidation through a variant Mars-van Krevelen mechanism while improving the N2 selectivity of NOx reduction. In addition, the abundant Brønsted acid sites from montmorillonite ensured the Cl-resistance and high stability of the catalyst. This study presents a novel approach for the synergistic removal of NOx and VOCs via tailoring atomically dispersed active sites of synergistic catalysts composed of complex oxides.</p
Elimination of NO<sub>x</sub> from Flue Gas in the Presence of Alkaline and Heavy Metals via Self-Protective Catalysts
Get PDFSelective catalytic reduction of NOx by ammonia under the exposure of alkaline and heavy metals in fly ash still remains a major challenge for NOx elimination among air pollution control. Herein, self-protective NOx reduction catalysts with remarkable alkaline and heavy metal resistance are originally designed by Ce and Cu dual active metal cations coexchanging attapulgite clays. It is revealed that the inherent Si-OH sites among attapulgite and partially exchanged Cu species effectively captured alkaline and heavy metal cation poisons through coordinate bonding or ion exchanging to protect the active components from being deactivated. Ultimately, highly efficient NOx reduction for stationary source flue gas catalytic purification is realized via the ingenious design of dual metal exchanged clay catalysts that own self-protective capacity to resist alkaline and heavy metal poisoning. This strategy paves the way for the development of low-temperature and high-efficiency denitrification catalysts with alkaline and heavy metal resistance for stationary source flue gas purification.</p
Improving Low-Cost Air Quality Monitoring: Developing User-Friendly Visualization Tools for Factor and Anomaly Identification, and Implementing Calibration Algorithms
No full textDigital therapeutics and behavioral chronic pain management:closing the gap between innovation and effective use
Get PDFRegulation of Intra-Nanopore Microenvironment in Oxygen-Rich Covalent Organic Frameworks for Enhanced Capacitive Deionization
Get PDFCapacitive deionization has emerged as a highly promising water treatment technology but is still limited by the low charge efficiency due to the co-ion expulsion effect. The precise modulation of the microenvironment at the electrode interface is crucial for boosting overall performance. In this work, the intra-nanopore microenvironment at oxygen-rich covalent organic frameworks electrode interface is precisely regulated by tuning charge density and hydrophilicity. The incorporation of hydroxyl groups manipulates the electronegativity of the electrode interface, significantly achieving strong adsorption with sodium ions as well as effectively minimizes the co-ions expulsion effect. Besides, the electrode exhibits enhanced hydrophilicity, which promotes more sodium ion transport and enrichment. Consequently, the prepared electrode demonstrates a high salt adsorption capacity of 47.7 mg g−1 and a charge efficiency of 0.87 at a voltage of 1.2 V in a 500 mg L−1 NaCl solution. The superior performance is confirmed to originate from the synergistic mechanism of the coordination ion exchange of hydroxyl and the redox reaction of carbonyl groups. This work offers new insights in establishing a feasible strategy to advance the efficiency and applicability of capacitive deionization and energy-related applications.</p
Evaluation methods for social housing projects supporting participatory and evidence-based decision-making
Get PDFInadequate infrastructure and low-quality public spaces in Social Housing Projects (SHP) negatively affect residents' well-being, compounded by a lack of participation that prioritizes cost reduction over user needs. Evidence-based design, common in healthcare, can improve SHP quality by integrating evidence into design processes, but its use is limited. This paper presents a study on evaluation methods, highlighting the recommended types of methods for participatory design processes and decision-making involving multidisciplinary stakeholders. A workshop with practitioners and academics examined the design and approval processes of SHPs, revealing issues such as market-driven priorities, unclear regulations, and insufficient collaboration, thus highlighting the need for more transparent and evidence-based approaches. A literature review also identified tools to align design decisions with user needs, but issues such as complexity, lack of knowledge, costs, and cultural barriers hinder their implementation. The research emphasizes the need to adapt these tools to the SHP context, fostering evidence integration and collaboration in housing projects
People-focused digital success metrics:Manufacturing leading the way for Employee Satisfaction and Diversity
Get PDFKaleidoscope:In-language Exams for Massively Multilingual Vision Evaluation
Get PDFThe evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While multilingual benchmarks have expanded, both in size and languages, many rely on translations of English datasets, failing to capture cultural nuances. In this work, we propose Kaleidoscope, as the most comprehensive exam benchmark to date for the multilingual evaluation of vision-language models. Kaleidoscope is a large-scale, in-language multimodal benchmark designed to evaluate VLMs across diverse languages and visual inputs. Kaleidoscope covers 18 languages and 14 different subjects, amounting to a total of 20,911 multiple-choice questions. Built through an open science collaboration with a diverse group of researchers worldwide, Kaleidoscope ensures linguistic and cultural authenticity. We evaluate top-performing multilingual vision-language models and find that they perform poorly on low-resource languages and in complex multimodal scenarios. Our results highlight the need for progress on culturally inclusive multimodal evaluation frameworks
Access Repository Dashboard
Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇