Process Integration Approaches to Improve the Techno-Economic Feasibility of Torrefaction Process

Over the past few years, the torrefaction process has evolved into a promising pre-treatment process to improve the properties of biomass to a level at which it is competitive with coal. However, in order to make torrefied biomass pellets an economically viable alternative to coal and wood pellets, the techno-economic feasibility of the torrefaction process needs to be improved. Thus, new process configurations are required to produce torrefied biomass pellets and other high value products from the torrefaction process. This thesis presents new process configurations, which have been evaluated with laboratory experiments, process simulations and mathematical modeling.Two different biomass samples i.e. eucalyptus clone and pinewood were used in torrefaction experiments. Initially, the effect that torrefaction pretreatment has on the kinetics, reaction mechanisms and heat flow during biomass pyrolysis was studied using TGA and DSC analysis. The results showed that the pyrolysis reaction mechanism varied significantly with torrefaction treatment. The heat flow data from DSC showed that torrefied biomass pyrolysis requires more energy than dried biomass in order to initiate the pyrolysis reactions.In the second stage, the anaerobic digestion of torrefaction condensate for the efficient utilization of torrefaction volatiles was studied through batch anaerobic digestion assays. Torrefaction condensate produced at 225, 275 and 300 °C was used at various substrate to inoculum ratio i.e. 0.1, 0.2 and 0.5. The methane yield was in the range of 430 - 492 mL/g volatile solids (VS) and 430 - 460 mL/g VS under mesophilic and thermophilic conditions, respectively. With the higher loading, i.e. > 0.2 VSsubstrate:VSinoculum, the production of methane was inhibited because of the inhibitory compounds in the torrefaction condensate, such as furfural and guaiacol.Large quantities of binders are required to make the pelletization process effective and to improve the quality of the pellets. An innovative process configuration is hereby proposed for detoxifying the torrefaction condensate and to reduce the binders’ requirement. The removal of a major inhibitory compound, i.e. furfural, through adsorption using torrefied biomass as an adsorbent was also studied. The adsorption of furfural from the torrefaction condensate at 250 g/L dosage was around 54%. Finally, the influence of the detoxification of the torrefaction condensate on the AD process was studied through batch assays.Finally, the experimental results were used to simulate industrial scale operations to evaluate the feasibility of integrating the torrefaction process with anaerobic digestion. In addition, different process integration approaches were studied to identify possible heat energy recovery options in the torrefaction process, on its own, and also when integrated with AD. The standalone torrefaction process was compared with three different process configurations, which varied according to the intended application for the produced biogas. The mass balance showed that biomethane can be produced at 369 m3/h, at 10 t/h of torrefied biomass pellets production capacity. A sensitivity analysis showed that the cost of the feedstock has a significant effect on the economics of the overall process. The economic analysis showed that the price of torrefied biomass pellets could be significantly reduced if the torrefaction process is integrated with AD

On demand multicast routing in wireless sensor networks

The wireless networking environment presents imposing challenges to the study of broadcasting and multicasting problems. Developing an algorithm to optimize communication amongst a group of spatially distributed sensor nodes in a WSN (Wireless Sensor Network) has been met with a number challenges due to the characterization of the sensor node device. These challenges include, but are not limited to: energy, memory, and throughput constraints. The traditional approach to overcome these challenges have emphasised the development of low power electronics, efficient modulation, coding, antenna design etc., it has been recognised that networking techniques can also have a strong impact on the energy efficiency of such systems. A variety of networking based approaches to energy efficiency are possible. One of the well-known approaches is to apply clustering techniques to effectively establish an ordered connection of sensor nodes whilst improving the overall network lifetime. This paper proposes an improved clustering based multicast approach that allows any cluster head to be a multicast source with an unlimited number of subscribers, to optimize group communication in WSNs whilst ensuring sensor nodes do not deprecate rapidly in energy levels. We review several clustering approaches and examine multicast versus broadcast communication in WSNs

Packet arrival analysis in wireless sensor networks

Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs

Does the assumption of exponential arrival distributions in wireless sensor networks hold?

Wireless Sensor Networks have seen a tremendous growth in various application areas despite prominent performance and availability challenges. One of the common configurations to prolong the lifetime and deal with the path loss phenomena having a multi-hop set-up with clusters and cluster heads to relay the information. Although researchers continue to address these challenges, the type of distribution for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. The general practice in published works is to compare an empirical exponential arrival distribution of wireless sensor networks with a theoretical exponential distribution in a Q-Q plot diagram. In this paper, we show that such comparisons based on simple eye checks are not sufficient since, in many cases, incorrect conclusions may be drawn from such plots. After estimating the Maximum Likelihood parameters of empirical distributions, we generate theoretical distributions based on the estimated parameters. By conducting Kolmogorov-Smirnov Test Statistics for each generated inter-arrival time distributions, we find out, if it is possible to represent the traffic into the cluster head by using theoretical distribution. Empirical exponential arrival distribution assumption of wireless sensor networks holds only for a few cases. There are both theoretically known such as Gamma, Log-normal and Mixed Log-Normal of arrival distributions and theoretically unknown such as non-Exponential and Mixed cases of arrival in wireless sensor networks. The work is further extended to understand the effect of delay on inter-arrival time distributions based on the type of medium access control used in wireless sensor networks

Packet Arrival Analysis in Wireless Sensor Networks

Distributed sensor networks have been discussed for more than 30 years, but the vision of Wireless Sensor Networks (WSNs) has been brought into reality only by the rapid advancements in the areas of sensor design, information technologies, and wireless networks that have paved the way for the proliferation of WSNs. The unique characteristics of sensor networks introduce new challenges, amongst which prolonging the sensor lifetime is the most important. WSNs have seen a tremendous growth in various application areas including health care, environmental monitoring, security, and military purposes despite prominent performance and availability challenges. Clustering plays an important role in enhancement of the life span and scalability of the network, in such applications. Although researchers continue to address these grand challenges, the type of distributions for arrivals at the cluster head and intermediary routing nodes is still an interesting area of investigation. Modelling the behaviour of the networks becomes essential for estimating the performance metrics and further lead to decisions for improving the network performance, hence highlighting the importance of identifying the type of inter-arrival distributions at the cluster head. In this paper, we present extensive discussions on the assumptions of exponential distributions in WSNs, and present numerical results based on Q-Q plots for estimating the arrival distributions. The work is further extended to understand the impact of end-to-end delay and its effect on inter-arrival time distributions, based on the type of medium access control used in WSNs. Future work is also presented on the grounds that such comparisons based on simple eye checks are insufficient. Since in many cases such plots may lead to incorrect conclusions, demanding the necessity for validating the types of distributions. Statistical analysis is necessary to estimate and validate the empirical distributions of the arrivals in WSNs

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

Process Integration Approaches to Improve the Techno-Economic Feasibility of Torrefaction Process

Over the past few years, the torrefaction process has evolved into a promising pre-treatment process to improve the properties of biomass to a level at which it is competitive with coal. However, in order to make torrefied biomass pellets an economically viable alternative to coal and wood pellets, the techno-economic feasibility of the torrefaction process needs to be improved. Thus, new process configurations are required to produce torrefied biomass pellets and other high value products from the torrefaction process. This thesis presents new process configurations, which have been evaluated with laboratory experiments, process simulations and mathematical modeling.Two different biomass samples i.e. eucalyptus clone and pinewood were used in torrefaction experiments. Initially, the effect that torrefaction pretreatment has on the kinetics, reaction mechanisms and heat flow during biomass pyrolysis was studied using TGA and DSC analysis. The results showed that the pyrolysis reaction mechanism varied significantly with torrefaction treatment. The heat flow data from DSC showed that torrefied biomass pyrolysis requires more energy than dried biomass in order to initiate the pyrolysis reactions.In the second stage, the anaerobic digestion of torrefaction condensate for the efficient utilization of torrefaction volatiles was studied through batch anaerobic digestion assays. Torrefaction condensate produced at 225, 275 and 300 °C was used at various substrate to inoculum ratio i.e. 0.1, 0.2 and 0.5. The methane yield was in the range of 430 - 492 mL/g volatile solids (VS) and 430 - 460 mL/g VS under mesophilic and thermophilic conditions, respectively. With the higher loading, i.e. > 0.2 VSsubstrate:VSinoculum, the production of methane was inhibited because of the inhibitory compounds in the torrefaction condensate, such as furfural and guaiacol.Large quantities of binders are required to make the pelletization process effective and to improve the quality of the pellets. An innovative process configuration is hereby proposed for detoxifying the torrefaction condensate and to reduce the binders’ requirement. The removal of a major inhibitory compound, i.e. furfural, through adsorption using torrefied biomass as an adsorbent was also studied. The adsorption of furfural from the torrefaction condensate at 250 g/L dosage was around 54%. Finally, the influence of the detoxification of the torrefaction condensate on the AD process was studied through batch assays.Finally, the experimental results were used to simulate industrial scale operations to evaluate the feasibility of integrating the torrefaction process with anaerobic digestion. In addition, different process integration approaches were studied to identify possible heat energy recovery options in the torrefaction process, on its own, and also when integrated with AD. The standalone torrefaction process was compared with three different process configurations, which varied according to the intended application for the produced biogas. The mass balance showed that biomethane can be produced at 369 m3/h, at 10 t/h of torrefied biomass pellets production capacity. A sensitivity analysis showed that the cost of the feedstock has a significant effect on the economics of the overall process. The economic analysis showed that the price of torrefied biomass pellets could be significantly reduced if the torrefaction process is integrated with AD

Advanced Applications of Torrefied Biomass: A Perspective View

Because of the social, economic, and environmental issues linked with fossil resources, there is a global interest in finding alternative renewable and sustainable resources for energy and materials production. Biomass could be one such renewable material that is available in large quantities. However, biomass physicochemical properties are a challenge for its industrial application. Recently, the torrefaction process was developed to improve the fuel characteristics of biomass. However, in recent days, energy production has slowly been shifting towards solar and wind, and restrictions on thermal power plants are increasing. Thus, there will be a need to find alternative market opportunities for the torrefaction industry. In that regard, there is a quest to find alternative applications of torrefaction products other than energy production. This paper presents a couple of alternative applications of torrefied biomass. Torrefaction process can be used as a biomass pretreatment option for biochemical conversion processes. The other alternative applications of torrefied biomass are using it as a reducing agent in metallurgy, as a low-cost adsorbent, in carbon-black production, and as a filler material in plastics. The use of torrefied biomass in fermentation and steel production is validated through a few laboratory experiments, and the results are looking attractive. The lower sugar yield is the main challenge in the case of the microbial application of torrefied biomass. The lower mechanical strength is the challenge in the case of using it as a reducing agent in a blast furnace. To date, very few studies are available in the literature for all the highlighted applications of torrefied biomass. There is a need for extensive experimental validation to identify the operational feasibility of these applications