Performance assessment and optimisation of a novel guideless irregular dew point cooler using artificial intelligence

Air Conditioners (ACs) are a vital need in modern buildings to provide comfortable indoor air for the occupants. Several alternatives for the traditional coolers are introduced to improve the cooling efficiency but among them, Evaporative Coolers (ECs) absorbed more attention owing to their intelligible structure and high efficiency. ECs are categorized into two types, i.e., Direct Evaporative Coolers (DECs) and Indirect Evaporative Coolers (IECs). Continuous endeavours in the improvement of the ECs resulted in development of Dew Point Coolers (DPCs) which enable the supply air to reach the dew point temperature. The main innovation of DPCs relies on invention of a M-cycle Heat and Mass Exchanger (HMX) which contributes towards improvement of the ECs’ efficiency by up to 30%. A state-of-the-art counter flow DPC in which the flat plates in traditional HMXs are replaced by the corrugated plates is called Guideless Irregular DPC (GIDPC). This technology has 30-60% more cooling efficiency compared to the flat plate HMX in traditional DPCs.Owing to the empirical success of the Artificial Intelligence (AI) in different fields and enhanced importance of Machine Learning (ML) models, this study pioneers in developing two ML models using Multiple Polynomial Regression (MPR), and Deep Neural Network (DNN) methods, and three Multi Objective Evolutionary Optimisation (MOEO) models using Genetic Algorithms (GA), Particle Swarm Optimisation (PSO), and a novel bio-inspired algorithm, i.e., Slime Mould Algorithm (SMA), for the performance prediction and optimisation of the GIDPC in all possible operating climates. Furthermore, this study pioneers in developing an explainable and interpretable DNN model for the GIDPC. To this end, a game theory-based SHapley Additive exPlanations (SHAP) method is used to interpret contribution of the operating conditions on performance parameters.The ML models, take the intake air characteristic as well as main operating and design parameters of the HMX as inputs of the ML models to predict the GIDPC’s performance parameters, e.g., cooling capacity, coefficient of performance (COP), thermal efficiencies. The results revealed that both models have high prediction accuracies where MPR performs with a maximum average error of 1.22%. In addition, the Mean Square Error (MSE) of the selected DNN model is only 0.04. The objectives of the MOEO models are to simultaneously maximise the cooling efficiency and minimise the construction cost of the GIDPC by determining the optimum values of the selected decision variables.The performance of the optimised GIDPCs is compared in a deterministic way in which the comparisons are carried out in diverse climates in 2020 and 2050 in which the hourly future weather data are projected using a high-emission scenario defined by Intergovernmental Panel for Climate Change (IPCC). The results revealed that the hourly COP of the optimised systems outperforms the base design. Moreover, although power consumption of all systems increases from 2020 to 2050, owing to more operating hours as a result of global warming, but power savings of up to 72%, 69.49%, 63.24%, and 69.21% in hot summer continental, arid, tropical rainforest and Mediterranean hot summer climates respectively, can be achieved compared to the base system when the systems run optimally

Investigation of a super performance dew point air cooler and its application in buildings

Based on extensive literature reviews, technical opportunities were identified to improve the energy efficiency of a dew point air cooler. This applied research aimed to develop a super-performance dew point air cooler to replace or partly replace the conventional energy-intensive air conditioners applicable to buildings.This research followed the methodology of combined theoretical and experimental investigation and a procedure of concept formation, validating and updating. A simulation software was developed and validated to investigate the impacts of the geometric configuration and operational conditions on the unit’s cooling performance and assist the prototype design. As a result, a novel dew point air cooler prototype, featuring innovative structure of the heat and mass exchanger, application of new materials and new processes, unique water distribution and control scheme and exclusive self-developed simulation software, was constructed and tested under controlled laboratory environment. Two patents were generated, one of which has been authorized by the China State Intellectual Property Office and the other has been filed in the Intellectual Property Office of the United Kingdom.Under standard testing conditions, i.e. dry-bulb temperature of 37.8oC and the coincident wet-bulb temperature of 21.1oC, the prototype cooler achieved a wet-bulb cooling effectiveness of 114% and dew-point cooling effectiveness of 75%, yielding a significantly high Coefficient of Performance (COP) of 52.5 at the optimal working air ratio of 0.364. The performance testing was also carried out under various simulated conditions representing the climates of hot & dry, warm & dry, moderate, warm & humid and the wet-bulb effectiveness of the prototype kept in the range 112% to 128% and dew-point effectiveness of 67%-76%, giving a COP of 37.4-52.5. Compared to the conventional vapour compression air conditioners which have a COP of around 3, the prototype cooler had 11-17 times higher COP, leading to a reduction in electrical power consumption by around 92% to 94%.A dedicated case study of the proposed dew point cooler based on conditions in Beijing, a representative city in warm and humid climate, was carried out to predict the annual operational performance, economic rewards, and associated environmental benefits. Compared to the conventional packaged air conditioners, 91.4% of annual power demand could be saved. The annual water consumption is less than 0.3 tonnes to provide the cooling of 2428.1 kWh. And the payback period of static investments would be less than 4 years to replace an equivalent packaged air conditioner.A significant leap forward has been achieved with this study and this is expected to open enormous global business in the very near future, thus bringing about great economic, environmental and sustainability benefits worldwide

Biomass Gasification and Applied Intelligent Retrieval in Modeling

Gasification technology often requires the use of modeling approaches to incorporate several intermediate reactions in a complex nature. These traditional models are occasionally impractical and often challenging to bring reliable relations between performing parameters. Hence, this study outlined the solutions to overcome the challenges in modeling approaches. The use of machine learning (ML) methods is essential and a promising integration to add intelligent retrieval to traditional modeling approaches of gasification technology. Regarding this, this study charted applied ML-based artificial intelligence in the field of gasification research. This study includes a summary of applied ML algorithms, including neural network, support vector, decision tree, random forest, and gradient boosting, and their performance evaluations for gasification technologies

Efficiently combining water reuse and desalination through Forward Osmosis-Reverse Osmosis (FO-RO) hybrids: a critical review

Forward osmosis (FO) is a promising membrane technology to combine seawater desalination and water reuse. More specifically, in a FO-reverse osmosis (RO) hybrid process, high quality water recovered from the wastewater stream is used to dilute seawater before RO treatment. As such, lower desalination energy needs and/or water augmentation can be obtained while delivering safe water for direct potable reuse thanks to the double dense membrane barrier protection. Typically, FO-RO hybrid can be a credible alternative to new desalination facilities or to implementation of stand-alone water reuse schemes. However, apart from the societal (public perception of water reuse for potable application) and water management challenges (proximity of wastewater and desalination plants), FO-RO hybrid has to overcome technical limitation such as low FO permeation flux to become economically attractive. Recent developments (i.e., improved FO membranes, use of pressure assisted osmosis, PAO) demonstrated significant improvement in water flux. However, flux improvement is associated with drawbacks, such as increased fouling behaviour, lower rejection of trace organic compounds (TrOCs) in PAO operation, and limitation in FO membrane mechanical resistance, which need to be better considered. To support successful implementation of FO-RO hybrid in the industry, further work is required regarding up-scaling to apprehend full-scale challenges in term of mass transfer limitation, pressure drop, fouling and cleaning strategies on a module scale. In addition, refined economics assessment is expected to integrate fouling and other maintenance costs/savings of the FO/PAO-RO hybrid systems, as well as cost savings from any treatment step avoided in the water recycling

Economic evaluation of seawater desalination : a case study analysis of cost of water production from seawater desalination in Saudi Arabia

As a result of the increasing scarcity of freshwater resources worldwide, many countries have resorted to the use of unconventional sources, of which seawater desalination is the most significant, for meeting the supply-demand gap. However, despite the recorded advances in desalination technologies of recent decades, desalination remains a very expensive operation and operators will be greatly assisted if reliable means of predicting the costs are available to aid effective decision making during planning of new plants or the operation of existing plants. To achieve this, it is important to fully understand the factors that contribute to desalination costs, which could then be used to develop appropriate models for predicting costs that can support budgeting and/or cost reductions decision making. Consequently, this project has investigated the development of such models for predicting monthly production costs using data from 16 operational plants in Saudi Arabia. Monthly and annual data spanning 2001 – 2010 were collected on total water production, type of desalination technique, sea water salinity, product water salinity, energy consumption, and total (capital and operational) unit cost of water production. Because of the way in which the data were archived, some of the variables only had the annual totals for some of the years, which made them unsuitable for the monthly scale adopted for the analyses. Consequently, disaggregation schemes based on several variants of the method of fragments widely used in hydrological studies were used to obtain monthly data from the annual data. Exploratory analysis showed that the monthly costs correlated most with the total water production, which then formed the lone independent variable for various tested regression model formulations. In general, an inverse regression model performed best during both calibration and validation. To enhance the usefulness of the predictive model for decision making, uncertainty limits of the predictions were constructed using a Monte Carlo simulation approach involving the seasonal, lag-1 autoregressive generation of equally likely realisations of the available historic records that have been transformed to remove the skewness. Extensive testing of the data generation technique showed that the assumed lag-1 auto-regressive dependence structure was adequate. This study thus provides for the first time a predictive model for costs of desalination in Saudi Arabia and its uncertainty range for effective budgeting and operational management. Although the models were developed using Saudi Arabia data, the fact that only one independent variable was used means that the replication of the methodology in other desalination-intensive countries can be readily carried out

Preparation of Rice Bran Protein Solutions Using a Water-Based Extraction Process

Rice bran (RB), which is a waste product of the rice industry, has great potential for use as a source of new protein supplements. In this study, the extraction of soluble proteins from rice bran was conducted using a water-based extraction method with the aid of sonication extraction and a hybrid sonication/thermal treatment approach, known as the soni-auto hybrid method. Both extraction methods were explored and compared to determine the most efficient extraction process using the one-factor-at-one-time (OFAT) method. The parameters studied and their experimental ranges for both extraction methods were as follows: sonication time = 5-45 min, sonication temperature = 30-80 °C, and feed-to-solvent ratio = 1:5-1:80 (g:mL). The most efficient extraction method was then used for optimization by means of response surface methodology (RSM) based on the central composite design (CCD) model. It was found that the soni-auto hybrid method exhibited a superior extraction performance compared with sonication alone, wherein the protein concentration was increased by up to 18% while maintaining a comparable quality. The use of this hybrid treatment approach also reduced the sonication time from 35 to 30 min and the sonication temperature from 50 to 45 °C. The optimal soni-auto hybrid conditions were determined by RSM to be a temperature of 50 °C, a feed-to-solvent ratio of 1:20, and an extraction time of 30 min; these conditions produced a protein concentration of 17.174 mg/mL. Finally, evaluation of the surface morphology and functional groups on the protein confirmed that the hybrid soni-auto approach provided a higher protein concentration without significantly affecting the protein structure or quality

Computational intelligence techniques for maximum energy efficiency of cogeneration processes based on internal combustion engines

153 p.El objeto de la tesis consiste en desarrollar estrategias de modelado y optimización del rendimiento energético de plantas de cogeneración basadas en motores de combustión interna (MCI), mediante el uso de las últimas tecnologías de inteligencia computacional. Con esta finalidad se cuenta con datos reales de una planta de cogeneración de energía, propiedad de la compañía EnergyWorks, situada en la localidad de Monzón (provincia de Huesca). La tesis se realiza en el marco de trabajo conjunto del Grupo de Diseño en Electrónica Digital (GDED) de la Universidad del País Vasco UPV/EHU y la empresa Optimitive S.L., empresa dedicada al software avanzado para la mejora en tiempo real de procesos industriale

Modelling and analysis methodology of SI IC engines turbocharged by VGT

[ES] Se espera que la nueva generación de motores de encendido provocado represente la mayor parte del mercado en el contexto de la propulsión de vehículos con o sin hibridación. Sin embargo, la tecnología actual todavía tiene desafíos críticos por delante para cumplir con los nuevos estándares de emisiones de CO2 y contaminantes. Consecuentemente están surgiendo nuevas tecnologías para mejorar la eficiencia de los motores y que estos cumplan con las nuevas normativas anti-contaminación. Entre otras, una de las tendencias más seguidas en la actualidad es la reducción de tamaño de los motores, concepto conocido como "downsizing", bajo la técnica de la turbosobrealimentación. Las nuevas tecnologías de turbocompresores, como las turbinas de geometría variable (TGV), se empiezan a considerar para su aplicación en las exigentes condiciones de funcionamiento de los nuevos motores de encendido provocado. En este trabajo, a partir de datos experimentales obtenidos en la sala de ensayos del motor, se propone una metodología de calibración del modelo completo de motor 1-D: se realiza un análisis teórico dirigido a asegurar el control total sobre cualquier aspecto de la simulación. En otras palabras, el modelo de motor 1-D se ajustó completamente con respecto a los datos experimentales del motor. Además, se demuestra la necesidad del postprocesamiento y validación de datos experimentales relacionados con mapas de turbocompresores, ya que se requiere desacoplar fenómenos como la transferencia de calor y las pérdidas por fricción de los denominados mapas experimentales de turbocompresores. De acuerdo con esto, se presenta una metodología para la obtención de mapas de turbocompresores, basada en una campaña experimental dividida en varias tipologias de ensayos y seguida de la etapa de modelado. La etapa de modelado se lleva a cabo utilizando modelos de turbocompresores integrales ya desarrollados o disponibles en la literatura. Adicionalmente se aborda la mejora en la precisión de las simulaciones cuando se comparan mapas de turbocompresores postprocesados con mapas puramente experimentales. Aprovechando el modelo de motor 1-D altamente validado y físicamente representativo así como los mapas validados del turbocompresor, se discute cómo las incertidumbres experimentales o las variables "fuera de control" pueden afectar los resultados experimentales. Se propone una metodología para superar este punto desde la perspectiva del modelado. Lo anterior permite realizar comparativas que en las se analiza exclusivamente el impacto de diferentes tecnologías de turbina o unidades de turbinas. Además, tomando como base el modelo ya desarrollado, es posible explorar diferentes cálculos de optimización, estrategias de control y proporcionar comparaciones de tecnología de turbinas en plenas cargas y cargas parciales de motor en un amplio rango de revoluciones. También se aborda el impacto de la altitud y se evalúan los transitorios de carga para dos tecnologías de turbinas analizadas: VGT y WG. Como conclusión, se demuestra que la tecnología VGT muestra menos limitaciones en condiciones de trabajo extremas, como en la curva de plena carga, donde la tecnología WG representa una limitación en términos de máxima potencia. Las diferencias a plena carga se vuelven aún más evidentes en condiciones de trabajo en altitud. Cuando se trata de cargas parciales, las diferencias en el consumo de combustible son menores, pero potencialmente beneficiosas para los VGT.[CA] S'espera que la nova generació de motors d'encesa per espurna representi la major part del mercat en el context de la propulsió de vehicles amb o sense hibridació. No obstant això, la tecnologia actual encara té reptes crítics per davant per complir amb els nous estàndards d'emissions de CO2 i contaminants. Conseqüentment estan sorgint noves tecnologies per millorar l'eficiència dels motors i que aquests compleixin amb les noves normatives anti-contaminació. Entre d'altres, una de les tendències més seguides en l'actualitat és la reducció de grandària dels motors, concepte conegut com "downsizing", sota la tècnica de la turbosobrealimentación. Les noves tecnologies de turbocompressors, com les VGT, es comencen a considerar per la seva aplicació en les exigents condicions de funcionament dels nous motors d'encesa per espurna. En aquest treball, a partir de dades experimentals obtingudes a la sala d'assajos de l'motor, es proposa una metodologia de calibratge del model complet de motor 1-D: es realitza una anàlisi teòrica dirigit a assegurar el control total sobre qualsevol aspecte de la simulació. En altres paraules, el model de motor 1-D es va ajustar completament respecte a les dades experimentals del motor. A més, es demostra la necessitat del posprocesamiento i validació de dades experimentals relacionats amb mapes de turbocompressors, ja que es requereix desacoblar fenòmens com la transferència de calor i les pèrdues per fricció dels denominats mapes experimentals de turbocompressors. D'acord amb això, es presenta una metodologia per a l'obtenció de mapes de turbocompressors, basada en una campanya experimental dividida en diverses tipologies d'assajos i seguida de l'etapa de modelatge. L'etapa de modelatge es porta a terme utilitzant models de turbocompressors integrals ja desenvolupats disponibles a la literatura. A més a s'aborda la millora en la precisió de les simulacions quan es comparen mapes de turbocompressors postprocessats amb mapes purament experimentals. Aprofitant el model de motor 1-D validat i físicament representatiu així com els mapes validats del turbocompressor, es discuteix com les incerteses experimentals o les variables "fora de control" poden afectar els resultats experimentals. Es proposa una metodologia per superar aquest punt des de la perspectiva de la modelització. L'anterior permet realitzar exclusivament la comparació de tecnologies / unitats de turbines. A més, prenent com a base el model ja desenvolupat, és possible explorar diferents càlculs d'optimització, estratègies de control i proporcionar comparacions de tecnologia de turbines a càrregues completes i parcials del motor en un ampli rang de revolucions del motor. També s'aborda l'impacte de l'altitud i s'avaluen els transitoris de càrrega per a dues tecnologies de turbines analitzades: VGT i WG. com a conclusió, es demostra que la tecnologia VGT mostra menys limitacions en condicions de treball extremes, com en la corba de plena càrrega, on la tecnologia WG representa una limitació en termes de màxima potència. Les diferències a plena càrrega es tornen encara més evidents en condicions de treball en altitud. Quan es tracta de càrregues parcials, les diferències en el consum de combustible són menors, però potencialment beneficioses per als VGT.[EN] The new generation of spark ignition (SI) engines is expected to represent most of the future market share in the context of power-train with or without hybridization. Nevertheless, the current technology has still critical challenges in front to meet incoming CO2 and pollutant emissions standards. Consequently, new technologies are emerging to improve engine efficiency and meet new pollutant regulations. Among others, one of the most followed trends is engine size reduction, known as downsizing, based on the turbocharging technique. New turbocharger technologies, such as variable geometry turbines (VGT), are evaluated for their application under the demanding operating conditions of SI engines. In this work, from experimental data obtained in an engine test cell, a 1-D complete engine model calibration methodology was conducted: a theoretical analysis aimed at ensuring full control on any aspect of the simulation. In other words, the 1-D engine model was fully fitted with respect to the experimental engine data. Furthermore, it is evidenced the requirement of post-processing and validating the experimental data dealing with turbocharger maps, since phenomena such as heat transfer and friction losses are required to be decoupled from the so-called experimental turbocharger maps. Accordingly, a methodology for turbocharger maps obtention is presented, based on an experimental campaign divided into several test typologies and followed by the modelling stage. The modelling stage is carried out making usage of already developed integral turbocharger models available in the literature. Additionally, the improvement in the accuracy of the simulations when post-processed turbocharger maps are compared against purely experimental maps is addressed. Taking advantage of the highly validated and physically representative 1-D gas-dynamics engine model and turbocharger validated maps, it is discussed how experimental uncertainties or "out-of-control" variables may impact the experimental results. A methodology is proposed to overcome this point from the modelling perspective. The previous allows performing exclusively turbine technologies/units comparison. In addition, taking as a basis the already developed model, it is possible to explore different optimization calculations, control strategies and provide turbine technology comparisons at engine full and partial loads in a wide range of engine speed. Also, the altitude impact is addressed and load transients are evaluated for two analysed turbine technologies: VGT and WG. In all, it was found that VGT technology shows fewer limitations in extreme working conditions, such as full load curve, where the WG technology represents a limitation in terms of the maximum power output. Full load differences become even more evident in altitude working conditions. When it comes to partial loads, differences in fuel consumption are minor but potentially beneficial for VGTs.Gómez Vilanova, A. (2022). Modelling and analysis methodology of SI IC engines turbocharged by VGT [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181929TESI

Assessing Biofiltration Pretreatment for Ultrafiltration Membrane Processes

An engineered biological filtration (biofiltration) process treating a nutrient-enriched, low-alkalinity, organic-laden surface water downstream of conventional coagulation-clarification and upstream of an ultrafiltration (UF) membrane process was assessed for its treatment effectiveness. The impact of biofiltration pretreatment on UF membrane performance was evaluated holistically by investigating the native source water chemistry and extending the analysis into the drinking water distribution system. The biofiltration process was also compared in treatment performance to two alternative pretreatment technologies, including magnetic ion exchange (MIEX®) and granular activated carbon (GAC) adsorption. The MIEX®, GAC adsorption, and biologically active carbon (BAC) filtration pretreatments were integrated with conventional pretreatment then compared at the pilot-scale. Comparisons were based on collecting data regarding operational requirements, dissolved organic carbon (DOC) reduction, regulated disinfection byproduct (DBP) formation, and improvement on the downstream UF membrane operating performance. UF performance, as measured by the temperature corrected specific flux or mass transfer coefficient (MTC), was determined by calculating the percent MTC improvement relative to the existing conventional-UF process that served as the control. The pretreatment alternatives were further evaluated based on cost and non-cost considerations. Compared to the MIEX® and GAC pretreatment alternatives, which achieved effective DOC removal (40 and 40 percent, respectively) and MTC improvement (14 and 30 percent, respectively), the BAC pretreatment achieved the lowest overall DOC removal (5 percent) and MTC improvement (4.5 percent). While MIEX® relies on anion exchange and GAC relies on adsorption to target DOC removal, biofiltration uses microorganisms attached on the filter media to remove biodegradable DOC. Two mathematical models that establish an empirical relationship between the MTC improvement and the dimensionless alkalinity to substrate (ALK/DOC) ratio were developed. By combining the biofiltration results from the present research with findings of previous studies, an empirical relationship between the MTC improvement versus the ALK/DOC ratio was modeled using non-linear regression in Minitab®. For surface water sources, UF MTC improvement can be simulated as a quadratic or Gaussian distribution function of the gram C/gram C dimensionless ALK/DOC ratio. According to the newly developed empirical models, biofiltration performance is optimized when the alkalinity to substrate ratio is between 10 and 14. For the first time a model has thus been developed that allows for a predictive means to optimize the operation of biofiltration as a pretreatment prior to UF membrane processes treating surface water