Predictive Models for Thermal Stability and Explosive Properties of Chemicals from Molecular Structure

Industrial chemical processes may involve thermal risks as most of the reactions performed are exothermic, the chemicals used are often thermally unstable, and the operating conditions are set to induce high conversion and throughput. Besides the reactive steps, all operations from mixing to storage and from processing to transport involving sensitive chemicals should be conducted under strictly controlled conditions ensuring safe operations. Performing an efficient risk assessment and implementing the proper risk mitigation measures are essential to avoid, or at least reduce, accidents and their potentially disastrous consequences. For optimal design and implementation of safety measures, it is important that these considerations are taken into account at early stages of process development. The required data should be made available at the appropriate time so it can be properly accounted for and efficiently serve the design. Yet, at early design phases, some information may be unavailable due to several reasons: the process design being still in development, some parameters can be unknown; experimental analysis of chemicals could be hindered or impossible due to products availability in required quantities; several alternatives are under investigation which raises the necessary resources (time and material) for experimental tests. Predictions would be the appropriate response to such scenario. The aim of this dissertation is to develop predictive models for two hazardous behaviors of chemicals: explosive sensitivity and thermal stability. For the models to be applicable at early development phases, it is preferable to minimize the information feed requirements, and therefore, structure-based approaches are applied. Two methods were identified: Quantitative Structure-Property Relationships (QSPR) and Group Contributions Method (GCM). The hazardous behaviors are studied through characteristic measurements: the Minimal Ignition Energy (MIE) to represent explosive sensitivity and Differential Scanning Calorimetry (DSC) for thermal stability. These measurements are widely employed in safety studies and deliver necessary information to identify potential hazards. Moreover, their specificities call for predictive models: MIE tests require repetitive analysis and hence are time and material consuming; regarding DSC experiments, experts have noted that they seem to exhibit structurally dependent features, and so far no study has comprehensively investigated this phenomenon. This work presents in a first part the structure-based approaches that are applied and the elements of Data Analysis necessary for developing predictive models and simulating experimental results. Secondly, both experimental analysis are detailed and the important information our models should be able to represent will be exposed. Finally, the third and last part is dedicated to the applications: the obtained predictive models are presented, evaluated and discussed. Most of the initial objectives are met as efficient solutions are proposed, nonetheless, some improvement strategies may also be considered.

Autogenous Shrinkage and Hydration Kinetics of SH-UHPFRC under Moderate to Low Temperature Curing Conditions

Mohammadhadi Kazemi Kamyab

Strain Hardening Ultra High Performance Fiber Reinforced Concrete (SH-UHPFRC) were used successfully over the last 8 years in numerous cast in place rehabilitation applications as long lasting waterproofing layers (20 to 30 mm thickness) and, combined with rebar, to increase the structural load bearing capacity of existing bridge decks or building slabs (50 to 70 mm thickness). In composite applications on reinforced concrete substrates, SH-UHPFRC provide a deformation capability (strain hardening) larger than their free shrinkage which makes localized macro cracking at service state very unlikely. On the other hand some specific conditions of microclimatic state of the substrate (moisture and thermal conditions) and climatological (temperature and humidity) of the site such as casting at low temperatures (winter conditions) might increase the autogenous shrinkage and thus eigenstresses of the freshly cast SH-UHPFRC and hinder the development of its tensile strength or/and deformability. Combination of these specific circumstances could compromise the SH-UHPFRC protective functions due to the occurrence of localized macro cracks, making the objective of using SH-UHPFRC as a onetime intervention strategy in rehabilitation application obsolete. Advancement in hydration at early age leads to formation of partially emptied capillary spaces contributing to self-desiccation, decrease of the relative humidity and increase of the capillary depression. Since water is under depression, the solid porous material is under compression forcing the material to shrink. From the aforementioned, it can be deduced that the autogenous shrinkage is a force driven phenomenon: a force is applied on the ageing viscoelastic porous skeleton and the apparent structural response of the bulk cementitious material is the autogenous shrinkage strain. Based on the aforementioned two levels of investigation were considered in this thesis: I. Material level: ageing viscoelastic porous skeleton of hydrating cementitious material II. Structural level: autogenous shrinkage development under the action of its driving forces The objective of this thesis was to study the development of the autogenous shrinkage and its relation with the development of microstructure and mechanical properties in SH-UHPFRC cured at moderate and low temperature conditions (1 to 20°C). Focus was put on: (1) kinetics and magnitude of hydration of silica fume and cement, (2) activation energy of the processes, (3) stiffness (E modulus and Poisson ratio) development, and (4) states of water and pore development. Finally a cross link analysis of information obtained from material and structural level was carried out to better highlight the mechanisms and driving forces of autogenous shrinkage. CM22-TKK, a SH-UHPFRC developed at MCS for rehabilitation applications, on the basis of CEMTECmultiscale® fibrous mixes, was used. Silica fume is one of the major constituents of CM22-TKK (26% by mass of cement). Extent of the silica fume pozzolanic reaction significantly affects the pore size distribution of the UHPFRC matrix which then influences the development of the relative humidity, self-desiccation and finally autogenous deformation. Detailed experimental investigation performed showed that only maximum 8% by mass of cement out of 26% silica fume used in the recipe reacts in moderate and low temperature curing conditions. Finally, a model of silica-fume degree of reaction as a function of curing temperature (5 to 250 °C) was proposed on the basis of a detailed literature survey of existing works with low W/B mixes. The activation energy of the thermo-mechanical properties was evaluated for thermo (cumulative heat of hydration) and mechanical properties development (such as dynamic Elastic modulus, dynamic Poisson’s ratio and compressive strength). A single activation energy Ea of 27.4 KJ/mol could successfully model the activation of all properties. Since maturity was not a proper reference to compare the autogenous deformations at various temperatures, a more fundamental reference such as degree of hydration was used. Experimental investigation was carried out using different techniques such as isothermal calorimetry and 29Si solid NMR to evaluate the development of the degree of hydration of cement and silica fume in UHPFRC at moderate and low temperature curing conditions. The ultimate degree of hydration of cement in CM22-TKK for a closed system was 0.34. There was a close correspondence between the experimental results and the predictions of the volumetric phase distribution models of Waller (0.28) and Jensen (0.32). Finally, the De Schutter et al. 1996 model was used to describe the mechanical properties (Emodulus and Poisson ratio) as function of degree of hydration. Nondestructive and non-invasive 1H-NMR was used to evaluate volumetric phase distribution development at 20°C, especially the classification of the water types (capillary, gel and C-S-H interlayer water) which brought fully new and valuable information about the hydration kinetics and pore size development. The results were also compared with Jensen volumetric phase distribution model to check the advantages and limitation of both approaches. Finally experimental investigation was carried out to follow the development of autogenous shrinkage and eigenstresses (in case of restrained shrinkage) of CM22-TKK cured in isotherm conditions (1 to 20°C). Eigenstresses were obtained and used to highlight the effect of the viscous response of the material at the different temperatures investigated. The previously mentioned results on the kinetics of the silica fume reaction, cement hydration and evolution of states of water and development of stiffness were then put into perspective with the trends observed on the autogenous shrinkage and eigenstresses development.

EPFL2013

Integrating rate based models into multi-objective optimisation of process designs using surrogate models

François Maréchal, Levent Sinan Teske

Multi-objective optimisation (MOO) of super-structured process designs are expensive in CPU- time because of the high number of potential configurations and operation conditions to be calculated. Thus single process units are generally represented by simple models like equilibrium based (chemical or phase equilibrium) or specific short cut models. In the development of new processes, kinetic effects or mass transport limitations in certain process units may play an important role, especially in multiphase chemical reactors. Therefore, it is desirable to represent such process unit by experimentally derived RBMs (rate based models) in the process flowsheet simulators used for the extensive MOO. This increases the trust engineers have in the results and allows enriching the process simulations with newest experimental findings. As most RBMs are iteratively solved, a direct incorporation would cause higher CPU-time that penalises the use of MOO. A global surrogate model (SUMO) of a RBM was successfully generated to allow its incorporation into a process design & optimisation (PDO) tool which makes use of an evolutionary MOO. The methodology was applied to a fluidised bed methanation reactor in the process chain from wood to Synthetic Natural Gas (SNG). Two types of surrogate model, an ordinary Kriging interpolation and an artificial neural network, were generated and compared to its underlying rate based model and the chemical equilibrium model. The analysis showed that kinetic limitations have significant influence on the result already for standard bulk gas chemical components. From experimental experience it can be stated that a significant amount of chemical compounds, which are near to complete conversion according the thermodynamic equilibrium, are measured in the gas phase after the reactor. Thus including RBMs in PDO improves the quality of results. This approach allows a significant improvement of information exchange between process design & optimisation workflow and experimental development of PUs in early stages of process development.

2013

Triple-mode grid-balancing plants via biomass gasification and reversible solid-oxide cell stack: Concept and thermodynamic performance

Chengzhou Li, Tzu-En Lin, François Maréchal, Maria del Mar Perez Fortes, Jan Van Herle, Ligang Wang, Yumeng Zhang

Biomass-to-electricity or -chemical via power-to-x can be potential flexibility means for future electrical grid with high penetration of variable renewable power. However, biomass-to-electricity will not be dispatched frequently and becomes less economically-beneficial due to low annual operating hours. This issue can be addressed by integrating biomass-to-electricity and -chemical via ‘‘reversible’’ solid-oxide cell stacks to form a triple-mode grid-balancing plant, which could flexibly switch among power generation, power storage and power neutral (with chemical production) modes. This paper investigates the optimal designs of such a plantconcept with a multi-time heat and mass integration platform considering different technology combinationsand multiple objective functions to obtain a variety of design alternatives. The results show that increasing plant efficiencies will increase the total cell area needed for a given biomass feed. The efficiency difference among different technology combinations with the same gasifier type is less than 5% points. The efficiency reaches up to 50%–60% for power generation mode, 72%–76% for power storage mode and 47%–55% for power neutral mode. When penalizing the syngas not converted in the stacks, the optimal plant designs interact with the electrical and gas grids in a limited range. Steam turbine network can recover 0.21–0.24 kW electricity per kW dry biomass energy (lower heating value), corresponding to an efficiency enhancement of up to 20%points. The difference in the amounts of heat transferred in different modes challenges the design of a common heat exchange network.