Catalytic activity evaluation of industrial Pd/C catalyst via gray-box dynamic modeling and simulation of hydropurification reactor

In this paper, dynamic modeling and simulation of the hydropurification reactor in a purified terephthalic acid production plant has been investigated by gray-box technique to evaluate the catalytic activity of palladium supported on carbon (0.5 wt.% Pd/C) catalyst. The reaction kinetics and catalyst deactivation trend have been modeled by employing artificial neural network (ANN). The network output has been incorporated with the reactor first principle model (FPM). The simulation results reveal that the gray-box model (FPM and ANN) is about 32 percent more accurate than FPM. The model demonstrates that the catalyst is deactivated after eleven months. Moreover, the catalyst lifetime decreases about two and half months in case of 7 percent increase of reactor feed flowrate. It is predicted that 10 percent enhancement of hydrogen flowrate promotes catalyst lifetime at the amount of one month. Additionally, the enhancement of 4-carboxybenzaldehyde concentration in the reactor feed improves CO and benzoic acid synthesis. CO is a poison to the catalyst, and benzoic acid might affect the product quality. The model can be applied into actual working plants to analyze the Pd/C catalyst efficient functioning and the catalytic reactor performance.

Studying industrial design : Exploring the experience of female students

Despite a significant increase in the number of women enrolling and graduating from design courses, the reality is that women remain ‘invisible’ in the design profession (Bruce, 1985). Over two decades ago, Bruce and Lewis (1990) argued that women were less likely than men to be designers due to three key gendered hurdles: the completion of a design degree, getting a design job and obtaining success in a design job. This paper focuses specifically on Australian women’s experience of hurdle one: the completion of a design degree, utilising industrial design as a case study. Semi-structured interview questions (exploring issues such as experience in class and the workshop, accessibility of the course and content, types of projects etc) were recorded and transcribed verbatim, with a thematic analysis conducted to better understand women’s experiences in completing their industrial design degree. This paper focuses on one key theme “navigating the design studio”, which comprises of three sub-themes: design skill development, the workshop experience and course evaluation. These findings highlight the need to understand the educational experience to ensure female designers remain motivated and eventually employable.

Industrial Designer

A discussion with Dr Rafael Gomez on Industrial Design for the Nelson Senior Graphics for Queensland Schools publication.

Bioaerosols associated with industrial green waste composting facilities and optimal microbiological indicators

This project developed and assessed a standard operating procedure for monitoring microbiological aerosol levels and dispersal from Australian industrial composting facilities. Development occurred via seasonal monitoring of such operations with evaluation of optimal microbial indicator organisms, sampling and analysis logistics. The resultant procedure allows practical end-user assessment of compost-associated bioaerosol levels, and potential health risks to proximal residential populations encroaching on such composting facilities and on-site industrial operations personnel.

How do experts think about statistics? Hints for improving undergraduate and postgraduate training

Experts are increasingly being called upon to quantify their knowledge, particularly in situations where data is not yet available or of limited relevance. In many cases this involves asking experts to estimate probabilities. For example experts, in ecology or related fields, might be called upon to estimate probabilities of incidence or abundance of species, and how they relate to environmental factors. Although many ecologists undergo some training in statistics at undergraduate and postgraduate levels, this does not necessarily focus on interpretations of probabilities. More accurate elicitation can be obtained by training experts prior to elicitation, and if necessary tailoring elicitation to address the expert’s strengths and weaknesses. Here we address the first step of diagnosing conceptual understanding of probabilities. We refer to the psychological literature which identifies several common biases or fallacies that arise during elicitation. These form the basis for developing a diagnostic questionnaire, as a tool for supporting accurate elicitation, particularly when several experts or elicitors are involved. We report on a qualitative assessment of results from a pilot of this questionnaire. These results raise several implications for training experts, not only prior to elicitation, but more strategically by targeting them whilst still undergraduate or postgraduate students.

Experiments and experiences with dependability for a large autonomous industrial vehicle

This paper describes the experiences gained performing multiple experiments while developing a large autonomous industrial vehicle. Hot Metal Carriers (HMCs) are large forklift-type vehicles used in the light metals industry to move molten or hot metal around a smelter. Autonomous vehicles of this type must be dependable as they are large and potentially hazardous to infrastructure and people. This paper will talk about four aspects of dependability, that of safety, reliability, availability and security and how they have been addressed on our experimental autonomous HMC.

Applying digital product memories in industrial production

Industrial production and supply chains face increased demands for mass customization and tightening regulations on the traceability of goods, leading to higher requirements concerning flexibility, adaptability, and transparency of processes. Technologies for the ’Internet of Things' such as smart products and semantic representations pave the way for future factories and supply chains to fulfill these challenging market demands. In this chapter a backend-independent approach for information exchange in open-loop production processes based on Digital Product Memories DPMs is presented. By storing order-related data directly on the item, relevant lifecycle information is attached to the product itself. In this way, information handover between several stages of the value chain with focus on the manufacturing phase of a product has been realized. In order to report best practices regarding the application of DPM in the domain of industrial production, system prototype implementations focusing on the use case of producing and handling a smart drug case are illustrated.

Estimates of lost material stock of buildings and roads due to the great east Japan earthquake and tsunami

This article describes research conducted for the Japanese government in the wake of the magnitude 9.0 earthquake and tsunami that struck eastern Japan on March 11, 2011. In this study, material stock analysis (MSA) is used to examine the losses of building and infrastructure materials after this disaster. Estimates of the magnitude of material stock that has lost its social function as a result of a disaster can indicate the quantities required for reconstruction, help garner a better understanding of the volumes of waste flows generated by that disaster, and also help in the course of policy deliberations in the recovery of disaster-stricken areas. Calculations of the lost building and road materials in the five prefectures most affected were undertaken. Analysis in this study is based on the use of geographical information systems (GIS) databases and statistics; it aims to (1) describe in spatial terms what construction materials were lost, (2) estimate the amount of infrastructure material needed to rehabilitate disaster areas, and (3) indicate the amount of lost material stock that should be taken into consideration during government policy deliberations. Our analysis concludes that the material stock losses of buildings and road infrastructure are 31.8 and 2.1 million tonnes, respectively. This research approach and the use of spatial MSA can be useful for urban planners and may also convey more appropriate information about disposal based on the work of municipalities in disaster-afflicted areas.

Wastewater pollution abatement in China: A comparative study of fifteen industrial sectors from 1998 to 2010

This study analyzes the management of wastewater pollutants in a number of Chinese industrial sectors from 1998 to 2010. We use decomposition analysis to calculate changes in wastewater pollutant emissions that result from cleaner production processes, end-of-pipe treatment, structural changes in industry, and changes in the scale of production. We focus on one indicator of water quality and three pollutants: chemical oxygen demand (COD), petroleum, cyanide, and volatile phenols. We find that until 2002, COD emissions were mainly reduced through end-of-pipe treatments. Cleaner production processes didn’t begin contributing to COD emissions reductions until the introduction of a 2003 law that enforced their implementation. Petroleum emissions were primarily lowered through cleaner production mechanisms, which have the added benefit of reducing the input cost of intermediate petroleum. Diverse and effective pollution abatement strategies for cyanide and volatile phenols are emerging among industries in China. It will be important for the government to consider differences between industries should they choose to regulate the emissions of specific chemical substances.

The practical potential of self-advocacy for improving safety outcomes for school-aged workers

Young workers are over-represented in workplace injury statistics and there is growing interest in addressing their vulnerability and safety exposure. Such concerns have been raised within a broader discursive framework of responsibilisation which has seen a transfer of responsibility for workplace safety from employer to worker. This article examines the potential for self-advocacy as a strategy for improving the safety of young workers through the provision of resources to articulate and act on workplace rights. The study utilises data derived from 48 group interviews involving 216 high school students (13–16 years of age) at 19 high schools in Queensland, Australia, who were asked to discuss their knowledge and experience of workplace rights and responsibilities. The limitations of the safety self-advocacy approach are explored, including the social, developmental and organisational issues that might affect the ability or willingness of school-aged workers to self-advocate. The findings reveal that the notion of self-advocacy is internalised by young people before they even enter the formal labour market but that in practice, attempts by young people to enact rights to safety are often dismissed or undermined.

A novel experimental method to assess industrial aerosol deposition in idealized porous channels

A novel and economical experimental technique has been developed to assess industrial aerosol deposition in various idealized porous channel configurations. This judicious examination on aerosol penetration in porous channels will assist engineers to better optimize designs for various engineering applications. Deposition patterns differ with porosity due to geometric configurations of the channel and superficial inlet velocities. Interestingly, it is found that two configurations of similar porosity exhibit significantly higher deposition fractions. Inertial impaction is profound at the leading edge of all obstacles, whereas particle build-up is observed at the trailing edge of the obstructions. A qualitative analysis shows that the numerical results are in good agreement with experimental results.

Introducing the practice of statistics: are we environmentally friendly?

The practice of statistics is the focus of the world in which professional statisticians live. To understand meaningfully what this practice is about, students need to engage in it themselves. Acknowledging the limitations of a genuine classroom setting, this study attempted to expose four classes of year 5 students (n=91) to an authentic experience of the practice of statistics. Setting an overall context of people’s habits that are considered environmentally friendly, the students sampled their class and set criteria for being environmentally friendly based on questions from the Australian Bureau of Statistics CensusAtSchool site. They then analysed the data and made decisions, acknowledging their degree of certainty, about three populations based on their criteria: their class, year 5 students in their school and year 5 students in Australia. The next step was to collect a random sample the size of their class from an Australian Bureau of Statistics ‘population’, analyse it and again make a decision about Australian year 5 students. At the end, they suggested what further research they might do. The analysis of students’ responses gives insight into primary students’ capacity to appreciate and understand decision making, and to participate in the practice of statistics, a topic that has received very little attention in the literature. Based on the total possible score of 23 from student workbook entries, 80 % of students achieved at least a score of 11.

Inferential, non-parametric statistics to assess quality of probabilistic forecast systems

Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

Post-industrial Intervention : An Activity-Theoretical Expedition Tracing the Proximal Development of Forms of Conducting Interventions

Ei saatavilla

From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.