Automated targeting approach for synthesis of heat exchanger network (HEN) with trigeneration system

AbstractIn this work, a novel systematic approach for the synthesis of heat exchanger network (HEN) with trigeneration system via multiple cascades automated targeting (MCAT) is presented. The optimisation objective is to locate the minimum total operating cost (TOC) of the system. The minimum hot and cold utilities of the HEN, allocation of utilities and potential power generation as well as the type of fuel can be determined via proposed approach. A case study of formic acid processing plant is solved to illustrate proposed approach

A systematic molecular design framework for an environmentally benign solvent recovery process

Computer Aided Molecular Design (CAMD) techniques have been extensively applied to design solvents for different applications. Most of the CAMD problems only aim at generating solvents that meet the predefined functionality. Nevertheless, it is important to consider the effect of solvent on the safety, health and environmental impacts during the recovery process. This paper presents a single stage CAMD framework that simultaneously quantifies the environmental impact of the solvent recovery process. The environmental impact of the process can be estimated through IChemE Sustainability Metrics. Besides, molecular properties that have an impact on the quantitative evaluation of the environmental impact of solvent recovery process are included in this framework. Weighted sum method coupled with Fuzzy Analytic Hierarchy Process (FAHP) weighting approach is employed to solve the multi-objective molecular design framework. A case study on solvent design for residual oil extraction from palm pressed fiber is presented to illustrate the proposed framework. In this work, only energy balance around multistage evaporator is incorporated into CAMD formulation as energy required to recover the solvent contributes to the largest portion of the whole process. The results show that the designed solvents simultaneously possess target functionalities and reduce the environmental impact of solvent recovery process

Guidelines for process safety hazard assessment based on process information

In any new chemical process development and design, process safety is a critical aspect to be considered besides economic and technical feasibility of the manufacture of the product. A lack of proper hazard assessment during the design phase may later result in accidents with disastrous consequences to workers, the public as well as the environment. Many methods have been introduced to qualitatively and quantitatively assess the safety level of processes. Despite the availability of a large amount of methods, a systematic framework that details guidelines for hazard identification, risk assessment, safety measure design, and safe critical decision-making is still missing. To address this issue, the main objective of this study was to propose a systematic framework that outlines comprehensive guidelines for assessing the safety performance of processes based on information from the piping and instrumentation diagram (P&ID). Apart from proposing the framework, appropriate strategies for minimizing safety hazards and risks are also recommended. In addition, the user is assisted in selecting the most appropriate assessment method according to his or her needs and the scope and constraints of the assessment. A case study is presented to illustrate the application of the proposed framework

Prediction and optimisation of syngas production from air gasification of Napier grass via stoichiometric equilibrium model

Napier grass is a promising candidate as a potential solid biofuel due to its wide availability, high growth rate, carbon neutrality and high volatility. Syngas is produced from gasification of Napier grass which can be further utilised for production of renewable fuel and other chemicals. The quality of the syngas produced from gasification of Napier grass is dependent on various factors such as operating temperature and pressure, gasification medium, biomass versus air ratio and moisture content. The optimisation of process parameters is important due to productivity and economic reasons. Experimental investigations to determine optimum conditions for gasification process are cost intensive and time consuming, rendering these techniques to be impractical. Thus, in this study, a stoichiometric equilibrium model for simulation of air gasification of Napier grass is developed. The model is modified to include correction factors at a series of temperatures and ERs which are multiplied with equilibrium constants to improve the accuracy of the model in predicting syngas and carbon compositions. The predicted values are in good agreement with experimental measurement, validating the model as a reliable tool for simulation of gasification performance. The modified model is further utilised to determine optimum operating conditions for maximum hydrogen production

Guidelines for Process Safety Hazard Assessment Based on Process Information

In any new chemical process development and design, process safety is a critical aspect to be considered besides economic and technical feasibility of the manufacture of the product. A lack of proper hazard assessment during the design phase may later result in accidents with disastrous consequences to workers, the public as well as the environment. Many methods have been introduced to qualitatively and quantitatively assess the safety level of processes. Despite the availability of a large amount of methods, a systematic framework that details guidelines for hazard identification, risk assessment, safety measure design, and safe critical decision-making is still missing. To address this issue, the main objective of this study was to propose a systematic framework that outlines comprehensive guidelines for assessing the safety performance of processes based on information from the piping and instrumentation diagram (P&ID). Apart from proposing the framework, appropriate strategies for minimizing safety hazards and risks are also recommended. In addition, the user is assisted in selecting the most appropriate assessment method according to his or her needs and the scope and constraints of the assessment. A case study is presented to illustrate the application of the proposed framework

Optimization and analysis for palm oil mill operations via input-output optimization model

A typical palm oil mill produces crude palm oil, crude palm kernel oil and other biomass from fresh fruit bunches. While the milling process is well established in the industry, insufficient research and development has been done on analyzing the operational performance of a mill. Factors such as operating time and fruit availability affect the performance of a palm oil mill (e.g., capital, operating and labor costs). This paper presents an input-output model to optimize the operations of a palm oil mill based on maximum economic performance. Following this, feasible operating range analysis (FORA) is performed to study the utilization and flexibility of the process. A palm oil mill case study in Malaysia is used to illustrate the proposed approach. Based on the optimized results, it was found that 37% reduction in capital cost and 49% increase in economic performance is achieved. Meanwhile, the utilization index of the mill during peak season increases from 0.48 to 0.76

Modelling and optimisation of biomass fluidised bed gasifier.

Recently, biomass for bioenergy and biofuel via gasification has become of great interest to energy and fuels production. Besides, gasification is recognised as a promising first processing step in an integrated biorefinery due to green and renewable technology. In this work, a stoichiometric equilibrium model of biomass fluidised bed gasifier is developed and followed by model improvement includes a correction factor to the equilibrium constants with a function of temperature. To illustrate the proposed model, bagasse is taken as the feedstock and gasification modelling based on the experiment result of a fluidised bed gasifier is presented. To ensure the accuracy of the model, predicted syngas compositions are validated with the experimental results. Besides, the proposed model is also reformulated for different types of biomass feedstock (e.g., rice husk, coconut shell, etc.). Based on the developed models, the operating condition of the gasifier can be optimised and the composition of the syngas can also be determined

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care