Syhthesise [sic] a sustainable sago industry

Various sago biomass (i.e., sago barks, fibres and wastewater) that potentially converted into value-added products are generated during sago starch extraction process (SSEP). In current industrial practices, such biomass are disposed to the environment and caused severe environmental issues. Therefore, in order to minimise the environmental impacts and to improve economic performance of sago industry, sago biomass is vital to be recovered. On the other hand, a sustainable sago value chain, which involved activities plantation, harvesting, sago starch extraction process (SSEP), and transportations, is synthesised in this thesis via Fuzzy Multi-Footprint Optimisation (FMFO) approach. This proposed approach considered carbon, water, and workplace footprints as well as economic performance of sago value chain. In order to trade-off the conflicts among the optimisation objectives, the concept of fuzzy optimisation is adopted in this approach. Then, recovery of sago biomass in SSEP is focused. In order to prioritise sago biomass for recovery in sago industry, Material Flow Cost Accounting (MFCA)-based prioritisation approach is developed in this thesis. This MFCA-based approach introduced hidden cost (HC) and carry-forward cost (CFC) to determine cost associated with waste streams. Based on the associated cost, waste streams can be prioritised for recovery. Then, this MFCA-based prioritisation approach is further extended as extended MFCA (eMFCA)-based approach to simultaneous synthesise total resource conservation network (RCN) with industrial processes. In this thesis, total water network and SSEP is synthesised simultaneously via eMFCA-based approach. Furthermore, techno-economic and environmental performance of conversion of sago barks and fibres into combined heat and power (CHP) and bioethanol is evaluated. In addition, sensitivity analysis on payback period is conducted in different scenarios due to variation of feedstock cost, enzyme cost, and labour cost. In order to further improve sustainability of sago industry, a conceptual integrated sago-based biorefinery (SBB) is envisaged. Maali’s method is adopted in this thesis to allocate the benefits of each party participating in integrated SBB. Lastly, conclusions and future works are included in the end of this thesis

Syhthesise [sic] a sustainable sago industry

Various sago biomass (i.e., sago barks, fibres and wastewater) that potentially converted into value-added products are generated during sago starch extraction process (SSEP). In current industrial practices, such biomass are disposed to the environment and caused severe environmental issues. Therefore, in order to minimise the environmental impacts and to improve economic performance of sago industry, sago biomass is vital to be recovered. On the other hand, a sustainable sago value chain, which involved activities plantation, harvesting, sago starch extraction process (SSEP), and transportations, is synthesised in this thesis via Fuzzy Multi-Footprint Optimisation (FMFO) approach. This proposed approach considered carbon, water, and workplace footprints as well as economic performance of sago value chain. In order to trade-off the conflicts among the optimisation objectives, the concept of fuzzy optimisation is adopted in this approach. Then, recovery of sago biomass in SSEP is focused. In order to prioritise sago biomass for recovery in sago industry, Material Flow Cost Accounting (MFCA)-based prioritisation approach is developed in this thesis. This MFCA-based approach introduced hidden cost (HC) and carry-forward cost (CFC) to determine cost associated with waste streams. Based on the associated cost, waste streams can be prioritised for recovery. Then, this MFCA-based prioritisation approach is further extended as extended MFCA (eMFCA)-based approach to simultaneous synthesise total resource conservation network (RCN) with industrial processes. In this thesis, total water network and SSEP is synthesised simultaneously via eMFCA-based approach. Furthermore, techno-economic and environmental performance of conversion of sago barks and fibres into combined heat and power (CHP) and bioethanol is evaluated. In addition, sensitivity analysis on payback period is conducted in different scenarios due to variation of feedstock cost, enzyme cost, and labour cost. In order to further improve sustainability of sago industry, a conceptual integrated sago-based biorefinery (SBB) is envisaged. Maali’s method is adopted in this thesis to allocate the benefits of each party participating in integrated SBB. Lastly, conclusions and future works are included in the end of this thesis

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

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Synthesis and Optimisation of A Sustainable Wastewater Treatment Plant via Material Flow Cost Account (MFCA)-based Approach

In this work, MFCA-based approach has been developed to synthesise an optimum wastewater treatment plant (WWTP). To develop the approach, a series of mathematical equations have been generated based on a generic superstructure that presented all possible pathways of WWTP. In this work, four continuous treatment stages (pre-treatment, chemical treatment, biological treatment and tertiary treatment) with various treatment technologies have been considered. In addition, raw material cost, energy cost, labour cost, and waste management cost as well as the hidden cost and carry-forward cost have also been considered in this approach. In this work, hidden cost is referred to the cost that associated with the process stream, while the carry-forward cost is referred to the cost that is carried forward from one process to another process. Furthermore, pollutants (e.g., TSS, COD, BOD and O&G) have also been considered to ensure the discharged water is complied with discharged regulations. To illustrate the developed approach, an industrial case study, has been solved. As results, an optimum sago wastewater treatment process with minimum waste generation cost is synthesised via a commercial optimisation software, LINGO

Design of Biomass Combined Heat and Power (CHP) Systems based on Economic Risk using Minimax Regret Criterion

It is a great challenge to identify optimum technologies for CHP systems that utilise biomass and convert it into heat and power. In this respect, industry decision makers are lacking in confidence to invest in biomass CHP due to economic risk from varying energy demand. This research work presents a linear programming systematic framework to design biomass CHP system based on potential loss of profit due to varying energy demand. Minimax Regret Criterion (MRC) approach was used to assess maximum regret between selections of the given biomass CHP design based on energy demand. Based on this, the model determined an optimal biomass CHP design with minimum regret in economic opportunity. As Feed-in Tariff (FiT) rates affects the revenue of the CHP plant, sensitivity analysis was then performed on FiT rates on the selection of biomass CHP design. Besides, design analysis on the trend of the optimum design selected by model was conducted. To demonstrate the proposed framework in this research, a case study was solved using the proposed approach. The case study focused on designing a biomass CHP system for a palm oil mill (POM) due to large energy potential of oil palm biomass in Malaysia