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A first-of-its-kind two-stage dew-point evaporative cooler with high energy efficiency and compact design
Get PDFThis research addresses the long-standing high working air ratio problem of conventional single-stage dew-point evaporative coolers (DPECs) by developing a first-of-its-kind two-stage DPEC. The system introduces a novel indirect cooling mechanism that distributes the cooling load across two sequential stages, significantly reducing the product air required for evaporation and enhancing energy efficiency. The key component of the cooler is a compact heat and mass exchanger capable of handling four fluid flows within a single unit, ensuring high performance and space efficiency. Tested under subtropical climate conditions, the developed two-stage DPEC demonstrated exceptional performance, preserving 88–90 % of the product air while maintaining its temperature below the wet-bulb and near the dew point. Additionally, it achieved a coefficient of performance (COP) of 15–17 under actual operating conditions, far surpassing conventional air conditioning systems. These results highlight its superior cooling capacity, energy efficiency, and compactness compared to existing single-stage M–cycle DPECs. The two-stage DPEC, with its high efficiency and compact design, is a scalable and sustainable cooling solution for real-world heating, ventilation, and air conditioning (HVAC) systems, offering significant energy savings and improved thermal comfort. This study underscores its potential as a transformative technology for reducing energy consumption and addressing cooling demands in subtropical and tropical climates.Energy Conversion and Managemen
The development of a framework for the implementation of industry 4.0 for Manufacturing in a developing country: a case study of Saudi Arabia
Get PDFObjective of the Research: The purpose of this research is to investigate Industry 4.0
implementation barriers in Small and Medium-Sized enterprises within the manufacturing sector
in developing countries. One of the objectives driving this research is the exploration of
associations between Industry 4.0 enablers and lean manufacturing. Further, the research aims to
construct a framework guiding stakeholders in implementing Industry 4.0 by overcoming common
barriers cited by experts in the field.
Research Problems: The main problem driving this research is the dearth of information on
Industry 4.0 implementation in developing countries. Simultaneously, little research has been
conducted to identify the barriers of industry 4.0 in SMEs within manufacturing realms in
emerging economies. Inadequate research investigated the associations between lean
manufacturing and industry 4.0 implementation.
Methodology: This is a mixed methods research study. On the qualitative side, focus
groups are used to collect open-ended responses to questions related to barriers facing the adoption
of Industry 4.0. Quantitatively, Interpretive Structural Modelling is used to construct the
framework driving stakeholders’ decisions to adopt and implement industry 4.0. Further, survey
research is used to validate experts' opinions on the utility of the ISM based model. In sum, three
distinct data collection techniques were used: (a) focus groups, (b) descriptive data for interpretive
structural modeling, and (c) survey responses. Based on the quantitative and qualitative methods
of data collection, a series of data analysis strategies were followed.
Key Findings: The current study reported strong associations linking Industry 4.0 enablers
and lean manufacturing outcomes. On the one hand, the use of Industrial Internet of Things (IIoT)
improved customers’ connectivity and engagement in each stage of the sustainable manufacturing
process. Thereby, improving customer satisfaction, a key element in measuring lean
manufacturing. Additionally, the deployment of cyber security as well as cloud computing
technology facilitates the transfer and storage of information minimizing the wasteful utilization
of physical and technical infrastructure, and manifestation of lean manufacturing practices. By the
same token, the increasing use of simulation and analytics technology minimizes the reliance on
manning thereby reducing further waste, the purpose of lean manufacturing.
Implications of the Research: Results of the ISM model were validated by using a
questionnaire showing the reliability and validity of the ISM constructed model that has been
adopted as the accepted framework guiding Industry 4.0 implementation. The proposed framework
in this study departs from existing models in significant ways. First, it does not prescribe sequential
steps since Industry 4.0 implementation is a complex process requiring simultaneous work from
various divisions across the organization. Second, the framework is scalable and flexible, allowing
it to fit many applications regardless of the size or nature of the industry. Third, the model
originated from contexts in developing countries, making it appropriate for implementation in
markets like Saudi Arabia.
Conclusion of the Research: This research concluded that the implementation of Industry
4.0 is neither straightforward nor linear. Experts voiced concern regarding the technical and
management infrastructures facing developing countries' manufacturing sectors. The research
suggested that the adoption of Industry 4.0 is a multi-step simultaneous process involving more
than a single practice overcoming several barriers at the same time.PhD in Manufacturin
Blast furnace gas utilization with calcium-assisted steel mill off-gas hydrogen production (CASOH) technology: technical evaluation
No full textIn pursuit of decarbonizing the iron and steel industry through the utilization of blast furnace gas (BFG), this study investigates the technical feasibility of a Ca–Cu looping technology known as calcium-assisted steel mill off-gas hydrogen production (CASOH). The process is modeled and analyzed using Aspen Plus software. The key technical performances of two versions of CASOH were evaluated and compared with more traditional solvent-based technology for the precombustion decarbonization of BFG using methyl diethanolamine (MDEA). The first case (base case, CASOH-B) uses part of the BFG to regenerate the sorbent; therefore, it concentrates CO2 up to 54%. In the second case (enhanced, CASOH-E), low-pressure steam is used for the calcination reaction. In the case of CASOH-B, the integration with a CO2 purification unit outperforms the other configurations regarding the CO2 capture efficiency, with values of up to 97% compared to 91% for CASOH-E and 83% for MDEA. However, CASOH-E demonstrated a significantly higher thermal output (224.5 MWLHV vs 77.6 MWLHV for CASOH-B), resulting in better cold gas efficiency and lower specific CO2 emissions (76% and 29.8 kgCO2/GJLHV for CASOH-E compared to 26.3% and 105.7 kgCO2/GJLHV for CASOH-B). Various scenarios were analyzed to meet the heat and power requirements of the process. When relying on an external energy source such as natural gas, biogas, or photovoltaic panels, the solvent-based case outperforms the CASOH configurations with a specific energy consumption per CO2 avoided (SPECCA) of 0.5–0.7 MJLHV/kgCO2, compared to 1.1–3.3 MJLHV/kgCO2 for CASOH configurations. However, if the hydrogen-rich stream produced in CASOH-E is used to meet energy demands, then CASOH-E becomes the most favorable option. These findings emphasize the importance of operational parameters in optimizing BFG decarbonization strategies by balancing thermal output, efficiency, and emissions capture.The authors would like to acknowledge the EPSRC for providing funding through the project BREINSTORM (Grant No. EP/S030654/1)The work was carried out as part of the European Union's Horizon 2020 research and innovation programme under grant agreement no. 884418 (C4U project).Industrial & Engineering Chemistry Researc
Optimization of heat transfer and deformation control in aluminum plate heat treatment: effect of nozzle inclination angle
No full textThe deformation behavior of an aluminum plate during heat treatment in an air-cushion furnace is numerically investigated, focusing on the effect of nozzle inclination angle. Validation of the numerical results was implemented with experimental data obtained from a specifically built experimental rig. The results reveal that at nozzle inclination angles of 30°, 45°, and 75°, the plate exhibits significant downward deflection in the central region, with the maximum deformation (60.3 mm) occurring at 45°. In contrast, a distinct wave-like deformation pattern with the minimal deformation (7.39 mm) arises at 60°, attributed to cross-flow interaction and the shear effect induced by plate motion. Consistency of the wave-like pattern is demonstrated at adjacent angles (57° and 62°). At an inclination angle of 60°, symmetric recirculating flows are reinforced, and the most uniform temperature distribution (average surface temperature of 463 K and temperature uniformity index of 0.757) is achieved. These findings highlight the critical role of nozzle inclination angle in reducing deformation and improving heat treatment quality, offering practical insights for industrial applications.The authors are grateful for the financial support from Priority Academic Program Development of Jiangsu Higher Education Institutions of China (PAPD) and Wuxi Science and Technology Development Fund (Grant No. G20212030).International Journal of Thermal Science
Experimental investigation of unsteady fan-intake interactions using time-resolved stereoscopic particle image velocimetry
Get PDFUnderstanding engine response to unsteady intake flow distortion is a crucial requirement to de-risk the development of novel aircraft configurations. This is more critical for configurations with highly embedded engines. Recent advances in non-intrusive, laser-based flow diagnostics demonstrated the ability to measure unsteady flows in convoluted intakes with high resolution in time and space. This work presents novel non-intrusive, unsteady flow measurements ahead of a fan rotor coupled to a convoluted diffusive intake. The fan rotor caused a local increase of the maximum levels of swirl intensity at the blade tip region, as well as flow re-distribution at the interface plane between the fan and the inlet duct compared to the baseline configuration with no fan in place. This contributed to the reduction of the overall swirl angle unsteadiness across the main flow distortion frequencies. This research presents a notable advance in unsteady fan-intake interaction characterisation. The work shows that high-resolution optical measurements offer notably better understanding of these complex aerodynamic interactions and have the potential to be part of larger scale, industrial testing programmes for future product development and certification.The SINATRA project leading to this publication has received funding from the Clean Sky 2 Joint Undertaking (JU) under grant agreement No 886521. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and the Clean Sky 2 JU members other than the Union.Experimental Thermal and Fluid Scienc
Assessing industry 4.0 readiness: a TOE-P framework for the sugar industry in developing economies
Get PDFIndustry 4.0 concepts have recently significantly supported transparency and reliability in every industrial sector. Organizations must adapt their traditional paradigms and approaches to align with market demands. Hence, developing a framework that can change these conventional approaches with fresh ideas is essential. The Industry 4.0 (I4.0) readiness model presents a creative concept that holds promise for the entire organizational and industrial value chain. Existing research focused only on technological, organizational, and environmental aspects. However, in process-extensive industries, like the sugar sector, the process is critical and considerably impacts the business. So, providing a strong framework for such sectors is necessary. The novelty of this paper is putting a process dimension in the TOE framework, which is critical for sugar industries. The study develops the extended framework to assess readiness. Experts have validated the framework as the study enhances it by adding process dimensions. Practitioners can apply the modeling concept to study the readiness framework in various sectors. Consequently, essential findings and recommendations drive the discussion forward. The study highlights opportunities for cross-disciplinary research across sectors.Discover Sustainabilit
A swarm architecture for small satellites pointing towards common targets
Get PDFThis paper proposes a leader-follower architecture for coordinating a swarm of satellites to observe stationary targets on the Earth's surface. Such a strategy uses the intersection of the line of sight of the distributed sensors as a key parameter to reconfigure and reorient the swarm satellites. Follower satellites receive the goal pointing and position of the leader satellite, to then autonomously calculate the required pointing direction to detect and observe the same targets. The performance of handling uncertainties due to communication delays on the pointing and position goals of the swarm is assessed and compensated via a Smith-like predictor. Simulation results demonstrate the viability of the proposed methodology for a typical small satellite swarm scenario.This research was funded by the NATO Science for Peace and Security Program under Grant No. MYP.G6141, Federated Laboratories Network for Testing Formations of Responsive
Satellites. (NATO Science for Peace and Security Program|MYP.G6141)15th IAA Symposium on Small Satellites for Earth System Observatio
When Multipath QUIC meets model predictive control and band sparse network coding: a novel multipathing solution for video streaming over heterogeneous wireless networks
No full textMultipath Quick UDP Internet Connections (MPQUIC) integrated with network coding offers a promising approach to improving the Quality of Experience (QoE) for video services over heterogeneous wireless networks. However, a significant challenge arises when encoding nodes transmit potentially redundant packets while awaiting decoding acknowledgments (ACKs) from endpoints. This behavior can limit effective transmission rates, thereby degrading real-time streaming performance and user QoE. In this paper, we propose MP2-QUIC, which addresses these challenges through a novel adaptive Model Predictive Control (MPC) framework for MPQUIC that optimizes both congestion window and encoding redundancy parameters via a discrete state transition model. By incorporating operating point linearization and leveraging the Central Limit Theorem, MP2-QUIC effectively enhances the control performance and effective throughput of the model in heterogeneous wireless network environments. MP2-QUIC further employs Band-Sparse Network Coding (Band-SNC) to minimize computational complexity at endpoints, while utilizing queuing theory principles to determine optimal encoded packet quantities. This integrated approach significantly enhances end-user QoE, and the experimental results demonstrate MP2-QUIC’s superior performance compared to existing MPQUIC encoding solutions, yielding a 68.85% reduction in peak decoding overhead and marked improvements in Peak Signal-to-Noise Ratio (PSNR).This work was supported in part by the Gan Po Talent Support Program-Academic and Technical Leaders Training Program in Major Disciplines of Jiangxi Province (Grant Number: 20243BCE51007), in part by the Natural Science Foundation of Jiangxi Province under Grant No. 20224ACB202007, and by the Graduate Innovation Fund of Jiangxi Normal University under Grant No. YJS2024060.IEEE Transactions on Broadcastin
Causal reinforcement learning for optimisation of robot dynamics in unknown environments
Get PDFAutonomous operations of robots in unknown environments are challenging due to the lack of knowledge of the dynamics of the interactions, such as the objects' movability. This work introduces a novel Causal Reinforcement Learning approach to enhancing robotics operations and applies it to an urban search and rescue (SAR) scenario. Our proposed machine learning architecture enables robots to learn the causal relationships between the visual characteristics of the objects, such as texture and shape, and the objects’ dynamics upon interaction, such as their movability, significantly improving their decision-making processes. We conducted causal discovery and RL experiments demonstrating the Causal RL’s superior performance, showing a notable reduction in learning times by over 24.5% in complex situations, compared to non-causal models.Engineering and Physical Sciences Research Council; EP/V026763/12024 IEEE International Smart Cities Conference (ISC2
Communication RSSI prediction and validation framework for advanced air mobility
Get PDFThis paper proposes a communication signal strength prediction and validation framework for the use of advanced air mobility. Advanced air mobility, including urban air mobility and unmanned aerial vehicles, requires a scalable, safe, and seamless communication infrastructure different from conventional aircraft. This paper proposes a hybrid regression-based prediction method that combines synthetic data generated from a ray-tracing model and real flight test data in the urban airspace and uses k-fold cross-validation to evaluate the predicted signal strength. The results show that the proposed framework provides reliable performance indices, effectively mitigating the insufficiency of flight data. This research will enable evaluating the communication infrastructure and identifying high-risk areas for advanced air mobility stakeholders.Innovate UKThis work was conducted as part of “Advanced Air Mobility: Communication Evaluation for Safe and Seamless Operations”, supported by Innovate UK (grant number 10117151) and Korea Agency for Infrastructure Technology Advancement (grant number RS-2024-00412531).2025 International Wireless Communications and Mobile Computing (IWCMC