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Influence of rapid heat treatment on the short‐term creep of high‐strength concrete Assembly of modular load‐bearing structures requires high precision geometry of precast concrete parts. Besides the manufacturing tolerances, transient, material‐related deviations due to shrinkage and creep must be taken into account. Regarding deformations [1] has already shown that rapid heat treatment significantly reduces shrinkage in high‐performance concretes. In this paper, the influence of heat treatment on creep deformation will be investigated. The focus is on short‐term creep within the first 28 days after concreting in order to mimic early construction stages experimentally. Heat treatment immediately after concreting in durations of 2, 4 and 24 h at 80 °C and 60 % RH as well as samples without heat treatment for reference are investigated. Loading starts 48 hours after concreting to cover minimum times between production and assembly. The experiments are performed on cylinders (D/H=100/200 mm) at load levels of 20 and 40 % of the early concrete strength. It is shown that heat treatment effectively reduces creep strains by up to 66 % (24 h) or 21 % (2 h), depending on the duration. Despite the high initial strength of the concrete, non‐linear creep is observed. The test results are generalized for different durations of heat treatment and load levels and processed into functional relationships by polynomial response surfaces. [ABSTRACT FROM AUTHOR]

Experiments on shrinkage reduction of high‐performance concrete components by heat treatment The paper investigates the shrinkage reduction of high‐performance concrete by heat treatment. Concretes are heat treated to accelerate hardening and to allow early stripping. Damage to the concrete structure is to be minimized by a suitable choice of maximum treatment temperature, heating and cooling rate. This leads to temperature durations of more than 24 h, which is not suitable for a serial production of precast concrete parts. For a minimally short heat treatment, a pre‐storage time and a regulated heating rate are omitted so that the heating starts directly after concreting. This shortening of the temperature duration has an influence on the shrinkage behavior. It is investigated here on prisms with and without steel fibers, as well as on beams with rebar ratios of 1.8 % and 3.1 %. All specimens are heat treated at 80 °C and 60 % relative humidity for 1, 2, 4, 6, and 24 h. Specimens without heat treatment serve as reference. The results show that the shrinkage strain is significantly reduced with increasing temperature duration. It also decreases with an increasing rebar ratio. In order to predict the shrinkage behavior as a function of temperature duration, data‐based response surfaces are derived and validated. Thereby, the prediction quality increases with increasing concrete age. [ABSTRACT FROM AUTHOR]

Characterizing the operation of a novel torrefaction plant based on horizontal moving bed reactors was the focus of this research work. Coppiced willow biomass was used as the feedstock for the torrefaction experiments carried out with this plant. The operating temperature and torrefaction residence time were each varied over a wide range in order to understand how these two parameters each influence torrefaction severity. The torrefaction severity was characterized by developing response surface plots for torrefaction metrics, including mass yield, energy yield, milling energy, and elemental composition. The operating conditions were varied from 220–280 °C with an 8–24 min residence time. The coppiced willow biomass was processed into a granular form, resulting in an average length and diameter of 19.3 and 7.5 mm, respectively. The operating conditions were found to produce a wide range of torrefaction severities with a mass yield range from 64.7–91.6 %. Temperature was found to have a greater influence over severity than exposure time. In order to understand the uncertainty of the measurements, experiments were repeated at a central point (250 °C and 16 min) six times. The repeatability was found to be ±0.72 % at the 95 % confidence limit. The response surfaces for mass and energy yield indicate that, for this feedstock, torrefaction severity below 80 % mass yield can be achieved in under 10 min at temperatures of 255 °C and above. This performance compares very favourably with other continuously fed pilot scale torrefaction plants. [ABSTRACT FROM AUTHOR]

The objective of this paper is to present the model‐based optimization results of an anaerobic granular sludge internal circulation reactor. The International Water Association Anaerobic Digestion Model No. 1 extended with phosphorus (P), sulfur (S), and ethanol is used to describe the main biological and physico‐chemical processes. The high‐rate conditions within the reactor are simulated using a flow + reactor model comprised of a series of continuous stirred tank reactors followed by an ideal total suspended solids separation unit. Following parameter estimation by least squares on the measured data, the model had a relative mean error of 13 and 15% for data set #1 and data set #2, respectively. Response surfaces show that the reactor performance index (a metric combining energy recovery in the form of heat and electricity, as well as chemicals needed for pH control) could be improved by 45% when reactor pH is reduced down to 6.8. Model‐based results reveal that influent S does not impose sufficient negative impacts on energy recovery (+5.7%, in MWh/day,+0.20 M€/year when influent S is removed) to warrant the cost of its removal (3.58 M€/year). In fact, the process could handle even higher S loads (ensuring the same degree of conversion) as long as the pH is maintained above 6.8. Nevertheless, a higher S load substantially increases the amount of added NaOH to maintain the desired operational pH (>25%) due to the acidic behavior of HS −. CO 2 stripping decreases the buffer capacity of the system and hence use of chemicals for pH control. Finally, the paper discusses the possibilities and limitations of the proposed approach, and how the results of this study will be put into practice. The objective of this paper is to present the model‐based optimization results of an anaerobic granular sludge internal circulation reactor. [ABSTRACT FROM AUTHOR]

Pt/γ-Al2O3 materials with different metal loading were prepared by incipient wetness impregnation method and tested as catalysts for hydrodeoxygenation (HDO) at 320 and 340°C with 4 and 5 h of reaction time. Oleic acid was used as model molecule in HDO process for biodiesel production, since this acid is in high proportion in waste vegetable oils used in food and agro-industrial processes. Increasing the Pt-nanoparticles (Pt-NPs) content influences on obtaining higher yields of n-C17 at optimal conditions of 335°C for 4.86 h of reaction and 4 nm of nanoparticle size, statistically determined. Yields of alkanes were theoretically optimized and using regression models for obtaining response surfaces with size (S) and distribution (V) of Pt-NPs as additional factors to temperature and reaction time. Interestingly, The Pt-nanoparticles parameters had a higher interaction with the rest of the other parameters for the n-C17 yield, suggested by a statistical P value less than 0.05. © 2017 American Institute of Chemical Engineers Environ Prog, 36: 1224-1233, 2017 [ABSTRACT FROM AUTHOR]

When optimizing a product or process with multiple responses, a two-stage Pareto front approach is a useful strategy to evaluate and balance trade-offs between different estimated responses to seek optimum input locations for achieving the best outcomes. After objectively eliminating non-contenders in the first stage by looking for a Pareto front of superior solutions, graphical tools can be used to identify a final solution in the second subjective stage to compare options and match with user priorities. Until now, there have been limitations on the number of response variables and input factors that could effectively be visualized with existing graphical summaries. We present novel graphical tools that can be more easily scaled to higher dimensions, in both the input and response spaces, to facilitate informed decision making when simultaneously optimizing multiple responses. A key aspect of these graphics is that the potential solutions can be flexibly sorted to investigate specific queries, and that multiple aspects of the solutions can be simultaneously considered. Recommendations are made about how to evaluate the impact of the uncertainty associated with the estimated response surfaces on decision making with higher dimensions. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A two-stage Pareto front approach can improve the process of making a decision about which input values simultaneously optimize multiple responses. However, ignoring estimation uncertainty and natural variability in the responses can potentially lead to suboptimal choices about those input values. A simulation-based approach is used to quantify and examine the impact that variability has on the superior solutions identified on the Pareto front and their performance. Because each optimization scenario has its own unique characteristics, including responses with different amounts of natural variability, the impact of variability on the solutions varies from situation to situation. We study how varying the amount of response variability affects the locations identified for the front and the characteristics of the most promising solutions on the front. We illustrate the method with an application involving process improvement through variance reduction. [ABSTRACT FROM AUTHOR]

To introduce Gaussian mixture distributions and sequential maximum a posteriori image segmentation (GM-SMAP) as a model that predicts species ranges from mapped climatic variables, and to compare its predictive capacity with two commonly used bioclimatic models: regression tree analysis (RTA) and smoothed response surfaces (SRS). North-west North America. We compared models for their ability to predict the distributional range of western hemlock ( Tsuga heterophylla). We calculated and projected nine climatic and water-balance variables to a 2-km grid up to 140 km from the T. heterophylla range. Models were trained using the five variables selected by RTA, as well as subsets of three variables. Goodness of fit was assessed using models trained and tested on the entire study area. Predictive capacity was assessed using 100 cross-validation tests, each trained on a randomly sampled 1% of the study area and tested on the complement of the study area. Models using all five variables were significantly better than three-variable models. Model fit was greatest for SRS. GM-SMAP misclassified slightly more area and RTA misclassified almost twice the area compared to SRS. However, cross- validation showed that the predictive capacity was clearly greatest for GM-SMAP and lowest for SRS, indicating that GM-SMAP makes more accurate predictions from sparse data. GM distributions prevent overfitting using an information-theoretic approach, and the SMAP algorithm minimizes the spatial extent of the largest misclassified area using a multiscale method. These properties, useful for image classification, also aid their strong predictive capacity as a bioclimatic model. SRS overfit the data, lowering its predictive capacity, and RTA failed to capture details of interactions among variables, yielding a poor fit. These results demonstrate the strong potential of GM-SMAP as a bioclimatic model. [ABSTRACT FROM AUTHOR]

In (designed) industrial experiments, the response observed often takes the form of a curve representing, for example, the evolution of a quality characteristic over a period of time. In such a context, the polynomial regression approach, usually used in response surface analysis to predict the response as a function of the experimental factors, should be adapted to the functional character of the response. This paper reviews several possible methods of analysing the results of a designed experiment when the response is a curve and compares them with a case study from the metal injection-moulding industry. Three different approaches are first presented to fit a model to the (functional) data: two-step nonlinear modelling; pointwise functional regression; and smoothed functional regression. All of the models derived are able to predict the functional response from any design factor setting chosen in the experimental domain. Two inferential problems are then discussed: the significance testing of experimental factor effects and the calculation of prediction intervals around predicted curves. Asymptotic results and bootstrap procedures are compared in this context. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Aim Document the biogeographical distributions of diatoms in the Canadian Arctic in relation to environmental factors. Location The Canadian Arctic Archipelago. Methods Diatoms were extracted from lake sediments and treated using standard methods. Rarefaction-estimated species richness, diatom concentrations (valves cc-1), and diatom abundance were mapped using a Geographic Information System. The physical and chemical parameters of the lakes were measured. Results A total of 326 taxa from 63 genera were found in 62 lakes of the study area. Up to 85 and as low as eight taxa were identified in any one lake, and rarefaction-estimated species richness correlated with lake size. Nearby lakes could have greatly different diatom assemblages. Many taxa showed limited distributions. Response surfaces and ordination techniques indicate that a large number of taxa prefer colder regions of the Arctic while the abundance of others was influenced by lake water chemical parameters such as TKN and SiO2. Main conclusions Although many taxa were common and found across the study area, diatom assemblages showed regional differences in the Arctic. Some taxa were not found in either the northern or southern parts of the Archipelago and others were restricted to particular regions. Newly delineated genera showed interpretable geographical patterns and could be related to environmental factors, suggesting that this more natural grouping may enhance our understanding of diatom ecology. Geographical, physical, and chemical factors are needed to explain diatom distributions in the Arctic. [ABSTRACT FROM AUTHOR]

Power tells us the probability of rejecting the null hypothesis for an effect of a given size and helps us select an appropriate design prior to running the experiment. The key to computing power for an effect is determining the size of the effect. We describe a general approach for sizing effects that covers a wide variety of designs including factorials with categorical levels, response surfaces, mixtures and crossed designs. Copyright © 2001 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary Projected climate change has been suspected of affecting the biota of conserved nature areas in different and significant ways. Nevertheless, strategic management within some nature conservation agencies appears relatively unprepared for the possible consequences of climate change. National level planning of reserve design networks has also tended to skirt the issue, possibly owing to insufficient analysis. This paper provides a first assessment of the possible effects of climate change on plant diversity within the protected area network of South Africa. A climate change scenario of increased temperature but no change in precipitation resulted in derived optimum growth days increasing in some reserves through increased temperature extending the growing season. In some other reserves optimum growth days declined through greater evapotranspiration. We concentrated on the larger reserves of the latter group for which conditions that are more limiting were predicted. Plant species were evaluated in terms of their critical limits in growth days and minimum temperature. Over a third of the species analysed for one reserve (Augrabies Falls National Park and Melkbosrand) was indicated to become locally extinct with climate change. Another reserve in the region showed fewer than 1% local extinctions. It is clear that although a certain magnitude of climate change is a prerequisite for these extinctions, the rate and number of extinctions depend strongly on the different environmental tolerances of the specific biotic components of the conserved area. Potential immigration of other species to Augrabies Falls/Melkbosrand required to balance the projected extinctions with climate change would need migration abilities and conditions that are unlikely to be met. A net decrease in plant diversity may thus be expected. The results confirm that with the climate change scenario used, the concept of sustaining species through fixed protected areas may be fundamentally... [ABSTRACT FROM AUTHOR]

The Taguchi methods have recently become popular in the U.S.A following a realization of their importance in Japanese quality design. This review is an initial attempt to extract the important ideas while drawing on the `Western' experience with response surface methodology and experimental design. [ABSTRACT FROM AUTHOR]