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This paper presents a novel Computer Aided Molecular Design (CAMD) methodology for the design of solvents with consideration of environmental impact during the extraction and recovery processes. Throughout the years, CAMD techniques have been widely applied to design novel molecules for various applications, especially solvents. Most of the works in this area are only focusing on designing solvents that can achieve its functionality. However, limited works consider safety, health and environmental impacts of the process in which the solvent is applied. In this work, a quantitative assessment of the total environmental burden for solvent recovery process is incorporated into a single stage CAMD framework. The CAMD formulation includes molecular properties that affect the quantitative assessment of the environmental impact of a process. A multi-objective solvent design framework is then solved using Fuzzy Analytic Hierarchy Process (FAHP) weighting approach to design solvents that satisfy various target properties. With this approach, the generated solvents can simultaneously improve the overall environmental characteristic of a process and give a better balance of performance for a set of predefined properties. To illustrate the proposed methodology, a case study on solvent design for residual oil extraction from palm pressed fibre is presented. [ABSTRACT FROM AUTHOR]

Tri-generation system is a facility which produces heat, power and cooling simultaneously from a single fuel source. In the industry, such system is commonly operated via two strategies; Following Electrical Load (FEL) or Following Thermal Load (FTL). However, these operating strategies may lead to huge amount of energy that is wasted. In this respect, several works have proposed a switching strategy, whereby tri-generation systems would interchange between FEL and FTL modes depending on energy demand. Unfortunately, the design of tri-generation based on this strategy has received limited attention. Besides, tri-generation operations often face challenges in equipment reliability. As tri-generation systems contain a network of interconnected equipment, equipment failures would disrupt the overall performance of a tri-generation system. As such, this work proposes a novel systematic optimisation approach to design a robust tri-generation system which can operate optimally in its operating strategies. In addition, the proposed approach can simultaneously determine type, size and required equipment redundancy (e.g. operating and standby units) of technologies while considering operating strategies in a tri-generation system. A palm biomass-based tri-generation system (BTS) case study is solved to illustrate the proposed approach. [ABSTRACT FROM AUTHOR]

Abstract: Synthesis and screening of technology alternatives is a key process-development activity in the process industries. Recently, this has become particularly important for the conceptual design of biorefineries. This work introduces a shortcut method for the synthesis and screening of integrated biorefineries. A structural representation (referred to as the chemical species/conversion operator) is introduced. It is used to track individual chemicals while allowing for the processing of multiple chemicals in processing technologies. The representation is used to embed potential configurations of interest. An optimization approach is developed to screen and determine optimum network configurations for various technology pathways using simple data. The solution to the optimization formulation provides a quick and effective method for screening and interconnecting the technological pathways and to distributing the flows over the network. Case studies are solved to illustrate the applicability of the proposed approach. [Copyright &y& Elsevier]

Abstract: Resource conservation networks (RCNs) are among the most effective systems for reducing the consumption of fresh materials and the discharge of waste streams. A typical RCN involves multiple elements of resource pre-treatment, material reuse/recycle, regeneration/interception, and waste treatment for final discharge. Due to the close interactions among these individual elements, simultaneous synthesis of a total RCN is necessary. This paper presents an optimisation-based procedure known as automated targeting technique to locate the minimum resource usage or total cost of a concentration- or property-based total RCNs. This optimisation-based approach provides the same benefits as conventional pinch analysis techniques in yielding various network targets prior to detailed design. Additionally, this approach offers more advantages than the conventional pinch-based techniques through its flexibility in setting an objective function and the ability to handle different impurities/properties for reuse/recycle and waste treatment networks. Furthermore, the concentration-based RCN is treated as the special case of property integration, and solved by the same model. Literature examples are solved to illustrate the proposed approach. [Copyright &y& Elsevier]

• The biomass supply chain offers a greener energy alternative to address the global warming issue. • Relationships among operators are important to the feasibility of a biomass supply chain. • Conflict analysis provides a mathematical framework to model relationships among individuals. • Conflict analysis was utilised in supply chain optimisation to capture the effect of the relationship to the supply chain. • Opimal supply chain using conflict analysis implied higher biomass consumption. Many policies have been rolled out to help biomass supply chains reach their greatest contribution to combat climate issues. However, policies are often undermined by the failure to capture the impact of policy on interactions among players in the supply chain. When players in the supply chain have different perspectives toward a given policy, it impacts the way they interact with one another. This was not considered in the existing literature. A conflict analysis approach is applied to evaluate the impact of the supply chain player's relationship on supply chain decisions. Conflict analysis can be incorporated to mathematically model the behaviours of each supply chain player towards specific proposals or policies. To illustrate the effectiveness of the proposed conflict analysis-embedded model, a case study on a biofuel supply chain based in Malaysia is analysed. In this study, players' reactions in the supply chain toward the three proposed government policies (transport subsidy, workforce reduction and production variation) are systematically modelled and used as an input for the supply chain optimisation. A comparison study is shown to benchmark the results obtained with and without conflict analysis. Based on the optimised results, the conflict analysis model called for a higher amount of empty fruit bunch (i.e., 2.7 times higher between empty fruit brunch sources and first layer storage) than the model without conflict analysis. The total cost associated with the supply chain also increased by 77% after relationships among players were considered (USD 4.5 million to USD 8.0 million). The higher cost and material from the model suggested that conflict reduces the effectiveness of material transfer by reducing the chances of successful trade within the supply chain. By foreseeing and considering the inefficiency of a supply chain in a model, policymakers can, therefore, possible to make more sound decisions. The proposed approach with these findings is crucial in notifying the policymakers of the true potential of their policy toward the supply chain. [ABSTRACT FROM AUTHOR]

Traditionally, the design of new chemical products for specific applications is done by using a combination of design heuristics, experimental studies and expert judgements. In addition to the conventional methods, chemical products can also be designed by using computer-aided molecular design (CAMD) techniques. Based on CAMD, optimal chemical products can be designed by identifying the molecule with the best properties that correspond with the target functionalities of the product. In general, the optimality of product property (termed as property superiority) is the only factor considered while designing optimal products by using CAMD techniques. However, it is noted that property prediction models are developed with certain accuracy and uncertainties. As the accuracy of property prediction models (termed as property robustness) can affect the effectiveness of CAMD techniques in predicting the product property, the effects of property prediction uncertainty have to be considered while applying CAMD techniques. This paper presents a systematic fuzzy optimisation based molecular design methodology. The methodology is developed for the design of optimum molecules used in chemical processes by considering and optimising both property superiority and robustness. Property superiority is quantified by property optimality. Meanwhile, property robustness is expressed by the standard deviation of the property prediction model, which is a measure of average variation between the experimental data and estimated values of product property using property prediction model. Fuzzy optimisation approach is extended in this work to address and trade off property superiority and robustness simultaneously. Molecular design technique is adapted in this work to identify the optimal molecular structure which satisfies multiple product specification. To illustrate the proposed method, a case study is presented where optimal solution is selected based on how much the solution satisfied the criteria of property superiority and robustness. [ABSTRACT FROM AUTHOR]

In this paper, a novel Computer Aided Molecular Design (CAMD) framework is developed to solve multi-objective molecular design problems. CAMD can be formulated as a multi-objective optimisation problem when there are multiple target properties to be optimised simultaneously. A major obstacle faced by multi-objective CAMD problems is the difficulty in assigning weighting factors to the target properties, since the relative importance of these factors is not always defined. It is particularly difficult to compare target properties which belong to different categories, such as physicochemical, safety, health and environmental properties, on a common scale. This paper presents a systematic CAMD algorithm built on Fuzzy Analytic Hierarchy Process (FAHP) to deal with the ambiguity involved in evaluating the weights of target properties in multi-objective CAMD problem. Instead of using exact numerical values, FAHP approach expresses the pairwise comparison of target properties through triangular fuzzy numbers, which allow the degree of confidence of decision maker to be quantified. Hence, the proposed approach can address the uncertainties arising from ambiguity involved during value judgement elicitation in multi-objective CAMD problems. The solutions generated provide a better balance of performance for a set of identified target properties. The proposed methodology is illustrated through a case study on designing a better solvent for extracting residual oil from palm pressed fibre. [ABSTRACT FROM AUTHOR]

Biomass is a sustainable source of energy which can be utilised to produce value-added products such as biochemical products and biomaterials. In order to produce a sustainable supply of such value-added products, an integrated biorefinery is required. An integrated biorefinery is a processing facility that integrates multiple biomass conversion pathways to produce value-added products. To date, various biomass conversion pathways are available to convert biomass into a wide range of products. Due to the large number of available pathways, various systematic screening tools have been developed to address the process design aspect of an integrated biorefinery. Process design however, is often inter-linked with product design as it is important to identify the optimal molecule (based on desired product properties) prior to designing its optimal production routes. In cases where the desired product properties cannot be met by a single component chemical product, a mixture of chemicals would be required. In this respect, product and process design decisions would be a challenging task for an integrated biorefinery. In this work, a novel two-stage optimisation approach is developed to identify the optimal conversion pathways in an integrated biorefinery to convert biomass into the optimal mixtures in terms of target product properties. In the first stage, the optimal mixture is designed via computer-aided molecular design (CAMD) technique. CAMD technique is a reverse engineering approach which predicts the molecules with optimal properties using property prediction models. Different classes of property models such as group contribution (GC) models and quantitative structure property relationship (QSPR) are adapted in this work. The main component of the mixture is first determined from the target product properties. This is followed by the identifying of additive components to form an optimal mixture with the main component based on the desired product properties. Once the optimal mixture is determined, the second stage identifies the optimal conversion pathways via superstructural mathematical optimisation approach. With such approach, the optimal conversion pathways can be determined based on different optimisation objectives (e.g. highest product yield, lowest environmental impact etc.). To illustrate the proposed methodology, a case study on the design of fuel additives as a mixture of different molecules from palm-based biomass is presented. With the developed methodology, optimal fuel additives are designed based on optimal target properties. Once the optimal fuel additives are designed, the optimal conversion pathways in terms of highest product yield and economic performance that convert biomass into the optimal fuel additives are identified. [ABSTRACT FROM AUTHOR]