Power Transient Analysis of Experimental Devices for Jules Horowitz Material Testing Reactor (JHR)

The objective of this thesis is the power transient analysis concerning experimental devices placed within the reflector of Jules Horowitz Reactor (JHR). Since JHR material testing facility is designed to achieve 100 MW core thermal power, a large reflector hosts fissile material samples that are irradiated up to total relevant power of 3 MW. MADISON devices are expected to attain 130 kW, conversely ADELINE nominal power is of some 60 kW. In addition, MOLFI test samples are envisaged to reach 360 kW for what concerns LEU configuration and up to 650 kW according to HEU frame. Safety issues concern shutdown transients and need particular verifications about thermal power decreasing of these fissile samples with respect to core kinetics, as far as single device reactivity determination is concerned. Calculation model is conceived and applied in order to properly account for different nuclear heating processes and relative time-dependent features of device transients. An innovative methodology is carried out since flux shape modification during control rod insertions is investigated regarding the impact on device power through core-reflector coupling coefficients. In fact, previous methods considering only nominal core-reflector parameters are then improved. Moreover, delayed emissions effect is evaluated about spatial impact on devices of a diffuse in-core delayed neutron source. Delayed gammas transport related to fission products concentration is taken into account through evolution calculations of different fuel compositions in equilibrium cycle. Provided accurate device reactivity control, power transients are then computed for every sample according to envisaged shutdown procedures. Results obtained in this study are aimed at design feedback and reactor management optimization by JHR project team. Moreover, Safety Report is intended to utilize present analysis for improved device characterization.

Automotive diesel engine transient operation: modeling, optimization and control

Traditionally, the study of internal combustion engines operation has focused on the steady-state performance. However, the daily driving schedule of automotive engines is inherently related to unsteady conditions. There are various operating conditions experienced by (diesel) engines that can be classified as transient. Besides the variation of the engine operating point, in terms of engine speed and torque, also the warm up phase can be considered as a transient condition. Chapter 2 has to do with this thermal transient condition; more precisely the main issue is the performance of a Selective Catalytic Reduction (SCR) system during cold start and warm up phases of the engine. The proposal of the underlying work is to investigate and identify optimal exhaust line heating strategies, to provide a fast activation of the catalytic reactions on SCR. Chapters 3 and 4 focus the attention on the dynamic behavior of the engine, when considering typical driving conditions. The common approach to dynamic optimization involves the solution of a single optimal-control problem. However, this approach requires the availability of models that are valid throughout the whole engine operating range and actuator ranges. In addition, the result of the optimization is meaningful only if the model is very accurate. Chapter 3 proposes a methodology to circumvent those demanding requirements: an iteration between transient measurements to refine a purpose-built model and a dynamic optimization which is constrained to the model validity region. Moreover all numerical methods required to implement this procedure are presented. Chapter 4 proposes an approach to derive a transient feedforward control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient.

A methodological approach for the performance optimization of transient seepage models through inverse analysis

The topic of the Ph.D project focuses on the modelling of the soil-water dynamics inside an instrumented embankment section along Secchia River (Cavezzo (MO)) in the period from 2017 to 2018 and the quantification of the performance of the direct and indirect simulations . The commercial code Hydrus2D by Pc-Progress has been chosen to run the direct simulations. Different soil-hydraulic models have been adopted and compared. The parameters of the different hydraulic models are calibrated using a local optimization method based on the Levenberg - Marquardt algorithm implemented in the Hydrus package. The calibration program is carried out using different types of dataset of observation points, different weighting distributions, different combinations of optimized parameters and different initial sets of parameters. The final goal is an in-depth study of the potentialities and limits of the inverse analysis when applied to a complex geotechnical problem as the case study. The second part of the research focuses on the effects of plant roots and soil-vegetation-atmosphere interaction on the spatial and temporal distribution of pore water pressure in soil. The investigated soil belongs to the West Charlestown Bypass embankment, Newcastle, Australia, that showed in the past years shallow instabilities and the use of long stem planting is intended to stabilize the slope. The chosen plant species is the Malaleuca Styphelioides, native of eastern Australia. The research activity included the design and realization of a specific large scale apparatus for laboratory experiments. Local suction measurements at certain intervals of depth and radial distances from the root bulb are recorded within the vegetated soil mass under controlled boundary conditions. The experiments are then reproduced numerically using the commercial code Hydrus 2D. Laboratory data are used to calibrate the RWU parameters and the parameters of the hydraulic model.