Estimation of concentration-dependent diffusion coefficient in drying process from the space-averaged concentration versus time with experimental data

The estimation of a concentration-dependent diffusion coefficient in a drying process is known as an inverse coefficient problem. The solution is sought wherein the space-average concentration is known as function of time (mass loss monitoring). The problem is stated as the minimization of a functional and gradient-based algorithms are used to solve it. Many numerical and experimental examples that demonstrate the effectiveness of the proposed approach are presented. Thin slab drying was carried out in an isothermal drying chamber built in our laboratory. The diffusion coefficients of fructose obtained with the present method are compared with existing literature results.

Approximation of Experimental Data by Bezier Curves

Very often the experimental data are the realization of the process, fully determined by some unknown function, being distorted by hindrances. Treatment and experimental data analysis are substantially facilitated, if these data to represent as analytical expression. The experimental data processing algorithm and the example of using this algorithm for spectrographic analysis of oncologic preparations of blood is represented in this article.

Experimental data of CO2, CO3, Omega calcite saturation, pH values, alpha and epsilon fractionation factors, and Dd18O calctite-water

The oxygen isotopic composition (d18O) of calcium carbonate of planktonic calcifying organisms is a key tool for reconstructing both past seawater temperature and salinity. The calibration of paloeceanographic proxies relies in general on empirical relationships derived from field experiments on extant species. Laboratory experiments have more often than not revealed that variables other than the target parameter influence the proxy signal, which makes proxy calibration a challenging task. Understanding these secondary or "vital" effects is crucial for increasing proxy accuracy. We present data from laboratory experiments showing that oxygen isotope fractionation during calcification in the coccolithophore Calcidiscus leptoporus and the calcareous dinoflagellate Thoracosphaera heimii is dependent on carbonate chemistry of seawater in addition to its dependence on temperature. A similar result has previously been reported for planktonic foraminifera, supporting the idea that the [CO3]2- effect on d18O is universal for unicellular calcifying planktonic organisms. The slopes of the d18O/[CO3]2- relationships range between -0.0243 per mil/(µmol/kg) (calcareous dinoflagellate T. heimii) and the previously published -0.0022 per mil/(µmol/kg) (non-symbiotic planktonic foramifera Orbulina universa), while C. leptoporus has a slope of -0.0048 per mil/(µmol/kg). We present a simple conceptual model, based on the contribution of d18O-enriched [HCO3]- to the [CO3]2- pool in the calcifying vesicle, which can explain the [CO3]2- effect on d18O for the different unicellular calcifiers. This approach provides a new insight into biological fractionation in calcifying organisms. The large range in d18O/[CO3]2- slopes should possibly be explored as a means for paleoreconstruction of surface [CO3]2-, particularly through comparison of the response in ecologically similar planktonic organisms.

Experimental data from column and batch samples

The presented thesis was written in the frame of a project called 'seepage water prognosis'. It was funded by the Federal Ministry for Education and Science (BMBF). 41 German institutions among them research institutes of universities, public authorities and engineering companies were financed for three years respectively. The aim was to work out the scientific basis that is needed to carry out a seepage water prognosis (Oberacker und Eberle, 2002). According to the Federal German Soil Protection Act (Federal Bulletin, 1998) a seepage water prognosis is required in order to avoid future soil impacts from the application of recycling products. The participants focused on the development of either methods to determine the source strength of the materials investigated, which is defined as the total mass flow caused by natural leaching or on models to predict the contaminants transport through the underlying soil. Annual meetings of all participants as well as separate meetings of the two subprojects were held. The department of Geosciences in Bremen participated with two subprojects. The aim of the subproject that resulted in this thesis was the development of easily applicable, valid, and generally accepted laboratory methods for the determination of the source strength. In the scope of the second subproject my colleague Veith Becker developed a computer model for the transport prognosis with the source strength as the main input parameter.

Experimental data on photophysiology and growth rates of the invasive foraminifera Amphistegina lobifera showing high thermal tolerance from the Eastern Mediterranean and the Gulf of Aqaba

Invasive species allow an investigation of trait retention and adaptations after exposure to new habitats. Recent work on corals from the Gulf of Aqaba (GoA) shows that tolerance to high temperature persists thousands of years after invasion, without any apparent adaptive advantage. Here we test whether thermal tolerance retention also occurs in another symbiont-bearing calcifying organism. To this end, we investigate the thermal tolerance of the benthic foraminifera Amphistegina lobifera from the GoA (29° 30.14167 N 34° 55.085 E) and compare it to a recent "Lessepsian invader population" from the Eastern Mediterranean (EaM) (32° 37.386 N, 34°55.169 E). We first established that the studied populations are genetically homogenous but distinct from a population in Australia, and that they contain a similar consortium of diatom symbionts, confirming their recent common descent. Thereafter, we exposed specimens from GoA and EaM to elevated temperatures for three weeks and monitored survivorship, growth rates and photophysiology. Both populations exhibited a similar pattern of temperature tolerance. A consistent reduction of photosynthetic dark yields was observed at 34°C and reduced growth was observed at 32°C. The apparent tolerance to sustained exposure to high temperature cannot have a direct adaptive importance, as peak summer temperatures in both locations remain <32°C. Instead, it seems that in the studied foraminifera tolerance to high temperature is a conservative trait and the EaM population retained this trait since its recent invasion. Such pre-adaptation to higher temperatures confers A. lobifera a clear adaptive advantage in shallow and episodically high temperature environments in the Mediterranean under further warming.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.

A comparison of predictions from the buildingEXODUS evacuation model with experimental data

Abstract not available

Development of a 1-D Catalyzed Diesel Particulate Filter Model for Simulation of the Performance and the Oxidation of Particulate Matter and Nitrogen Oxides Using Passive Oxidation and Active Regeneration Engine Experimental Data

Back-pressure on a diesel engine equipped with an aftertreatment system is a function of the pressure drop across the individual components of the aftertreatment system, typically, a diesel oxidation catalyst (DOC), catalyzed particulate filter (CPF) and selective catalytic reduction (SCR) catalyst. Pressure drop across the CPF is a function of the mass flow rate and the temperature of the exhaust flowing through it as well as the mass of particulate matter (PM) retained in the substrate wall and the cake layer that forms on the substrate wall. Therefore, in order to control the back-pressure on the engine at low levels and to minimize the fuel consumption, it is important to control the PM mass retained in the CPF. Chemical reactions involving the oxidation of PM under passive oxidation and active regeneration conditions can be utilized with computer numerical models in the engine control unit (ECU) to control the pressure drop across the CPF. Hence, understanding and predicting the filtration and oxidation of PM in the CPF and the effect of these processes on the pressure drop across the CPF are necessary for developing control strategies for the aftertreatment system to reduce back-pressure on the engine and in turn fuel consumption particularly from active regeneration. Numerical modeling of CPF's has been proven to reduce development time and the cost of aftertreatment systems used in production as well as to facilitate understanding of the internal processes occurring during different operating conditions that the particulate filter is subjected to. A numerical model of the CPF was developed in this research work which was calibrated to data from passive oxidation and active regeneration experiments in order to determine the kinetic parameters for oxidation of PM and nitrogen oxides along with the model filtration parameters. The research results include the comparison between the model and the experimental data for pressure drop, PM mass retained, filtration efficiencies, CPF outlet gas temperatures and species (NO2) concentrations out of the CPF. Comparisons of PM oxidation reaction rates obtained from the model calibration to the data from the experiments for ULSD, 10 and 20% biodiesel-blended fuels are presented.

Study of risky situations using experimental data coming from an instrumented bicycle

The aim of this master’s thesis is to study the risky situations of the cyclist when they interact with road infrastructure and other road users as well as the influence of speed on safety. This research activity is linked with the SAFERUP (Sustainable, Accessible, Resilient, and Smart Urban Pavement) European funded project where one of the doctoral candidate has performed experiments on the bicycle simulation at the Gustave Eiffel university in the PICS-L laboratory (Paris) and instrumented bicycle at the Stockholm (Sweden). The approach of the experiment was to hire a number of people who have participated in the riding of the Instrumented bicycle (Stockholm) and bicycle simulator (PICS-L) which were developed by attaching different sensors and devices to measure important parameters of the bicycle riding and their data was collected to analysis in order to understand the behavior of the cyclist to improve the safety. In addition, a mobile eye tracker wore by participants to record the real experiment scenario, and after the end of the trip, each participant shared their remarks regarding their experience of bicycle riding according to different portions of the road infrastructure. In this research main focus is to analyze the relevant data such as speed profiles, video recordings and questionnaire surveys from the instrumented bicycle experiment. In fact, critical situations, where there was a higher probability, were compared with the subjective evaluation of the participant to be conscious of the issues related to the safety and comfort of the cyclist in different road characteristics.

Probabilistic evidential assessment of gunshot residue particle evidence (Part II) : Bayesian parameter estimation for experimental count data.

Part I of this series of articles focused on the construction of graphical probabilistic inference procedures, at various levels of detail, for assessing the evidential value of gunshot residue (GSR) particle evidence. The proposed models - in the form of Bayesian networks - address the issues of background presence of GSR particles, analytical performance (i.e., the efficiency of evidence searching and analysis procedures) and contamination. The use and practical implementation of Bayesian networks for case pre-assessment is also discussed. This paper, Part II, concentrates on Bayesian parameter estimation. This topic complements Part I in that it offers means for producing estimates useable for the numerical specification of the proposed probabilistic graphical models. Bayesian estimation procedures are given a primary focus of attention because they allow the scientist to combine (his/her) prior knowledge about the problem of interest with newly acquired experimental data. The present paper also considers further topics such as the sensitivity of the likelihood ratio due to uncertainty in parameters and the study of likelihood ratio values obtained for members of particular populations (e.g., individuals with or without exposure to GSR).

A set of canonical problems in sloshing. Part 0: Experimental setup and data processing

In a series of attempts to research and document relevant sloshing type phenomena, a series of experiments have been conducted. The aim of this paper is to describe the setup and data processing of such experiments. A sloshing tank is subjected to angular motion. As a result pressure registers are obtained at several locations, together with the motion data, torque and a collection of image and video information. The experimental rig and the data acquisition systems are described. Useful information for experimental sloshing research practitioners is provided. This information is related to the liquids used in the experiments, the dying techniques, tank building processes, synchronization of acquisition systems, etc. A new procedure for reconstructing experimental data, that takes into account experimental uncertainties, is presented. This procedure is based on a least squares spline approximation of the data. Based on a deterministic approach to the first sloshing wave impact event in a sloshing experiment, an uncertainty analysis procedure of the associated first pressure peak value is described.

Liquid–Liquid, Vapor–Liquid, and Vapor–Liquid–Liquid Equilibrium Data for the Water–n-Butanol–Cyclohexane System at Atmospheric Pressure: Experimental Determination and Correlation

The temperature and the composition of the vapor–liquid–liquid equilibrium (VLLE) and the vapor–liquid equilibrium (VLE) of a ternary mixture of water–n-butanol–cyclohexane were measured at atmospheric pressure (101.32 kPa) in a modified dynamic recirculating still. As found in the literature, the experimental data obtained reveal a ternary azeotrope at 341.86 K with a mole fraction composition of 0.281, 0.034, and 0.685 water, n-butanol, and cyclohexane, respectively. The liquid–liquid equilibrium (LLE) compositions were measured at a constant temperature of 313.15 K and compared with data in the literature collected at other temperatures. Thermodynamic consistency of all the experimental data was demonstrated. The universal quasichemical (UNIQUAC) and the nonrandom two-liquid (NRTL) thermodynamic models were used to correlate the VLE and LLE data, while the original universal functional (UNIFAC) model was used to compare the predicted data.