Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method.

We present the validation of the hybrid sSSA-SDPD method for advection-diffusion-reaction problems coupled to discrete biochemical systems, as presented in the publication "A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems" (Drawert et al., 2019). We validate 1D diffusion, and 2D diffusion cases against their analytical solutions. We present graphs and tables of data showing the error in the simulation method

Validation data for a hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) method

We present the validation of the hybrid sSSA-SDPD method for advection-diffusion-reaction problems coupled to discrete biochemical systems, as presented in the publication “A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems” (Drawert et al., 2019). We validate 1D diffusion, and 2D diffusion cases against their analytical solutions. We present graphs and tables of data showing the error in the simulation method

Multiscale analyses of cellular signaling and regulation in response to multiple stress conditions

Understanding the relationship between signaling and its corresponding cellular response is critical to combating stress responses, especially responses related antibiotic resistance and non-genetic phenotypic transitions to antibiotic tolerance. However, bacterial signal responses are notoriously noisy and difficult to predict. This work first develops a multiscale cell cycle-aware signal modeling framework to explore the energetics and dynamics of the phosphate starvation stress response two-component system, PhoBR, to better understand the relationship between stress response proteins and the bounds of cellular memory in stress response. I found that the transcription factor responsible for stress response remains nominally “active” for 2-4 generations after the stress response is relieved due to sequestration effects, with differential memory in offspring cells dictated by stochastic protein inheritance. Next, I studied a novel antibiotic persister phenotype that arises in non-canonical conditions. This phenotype exhibited a previously unknown stress response that resulted in growth arrest, granting it antibiotic tolerance. The tolerance seems to be imparted by a global stress response arising from toxic excessive lactose import, seemingly opposite of the starvation response that induces canonical persister cell formation. Finally, I improved the PhoBR stress response model to measure stochastic fluctuations of proteins within the two-component system to identify the principles of signal fluctuations and how they drive variability in the bacterial cell cycle (i.e., growth rate). The downstream regulon of the PhoB response regulator is the main driver of the growth rate, but the transcriptionally active dimerized PhoB acts as the link between fast molecular fluctuations and slower gene expression fluctuations within the system. Finally, I present a vision for future developments of this style of modeling to include spatial information

Методологија за синтезу реактора заснована на концептима интензификације процеса и примени метода оптимизације

In this Ph.D. thesis, a new methodology for Reactor Synthesis Based on Process Intensification Concepts and Application of Optimization Methods (ReSyPIO) is presented and applied to two different cases. In Chapter 1: Introduction – Motivation and Objectives, the motive for the research is presented, and Hypotheses are formulated. The ReSyPIO methodology that rests upon these Hypotheses and consists of three consecutive stages is briefly described in this Chapter. The first stage encapsulates all present phases and phenomena inside the reactor functional building block, called module. Modules come as a direct result of a conceptual representation of the analyzed system. In the second stage, modules are further segmented if needed and interconnected, creating a reactor superstructure that is mathematically described for all desirable operating regimes. In the last stage of the ReSyPIO methodology, the optimal structure, operating conditions, and the operational regime are determined with the use of rigorous optimization. All three stages of the ReSyPIO methodology have a backflow, meaning that if analysis leads to impractical, nonfunctional or inefficient results, modifications in reactor superstructure and modules can be made. The objective is to conceptually and numerically derive the most efficient reactor structure and a set of operating conditions that would be used as a starting point in the future reactor design. Chapter 2: Literature Review is used to cover and review the most important research published in the area of Process Intensification and different Process System Engineering techniques. Different approaches and studies present in academia are highlighted and their elements compared with the presented ReSyPIO methodology with the accent on its advantages and contribution to the engineering science community.Also, in this Chapter, an array of well researched analytical and numerical approaches is presented that could be used in the future to strengthen the ReSyPIO methodology further and facilitate its easier application. In Chapter 3: Description of the ReSyPIO Methodology Reactor Synthesis based on Process Intensification and Optimization of Superstructure is explained in detail, with a graphical representation of the main building block, called Phenomenological Module. A general explanation is given on how to form a reactor superstructure and mathematically describe it with sets of material and energy balance equations that correspond to a number of present phases and components in the system. The ReSyPIO methodology is first applied to a generic case of two parallel reactions in Chapter 4, called Application of the ReSyPIO Methodology on a Generic Reaction Case. The case corresponds to two parallel reactions that could be found in the fine chemical industry. The reactions are endothermic and slow with the undesired product. After the application of the ReSyPIO methodology, an optimal reactor structure consisting of a segmented module with 17 side inlets for the reactant and heat source is obtained. It is recommended for the reactor to work in a continuous steady-state mode as the dynamic operation would not lead to a sufficient increase in reactor efficiency...У овој докторској дисертацији је представљена и примењена нова методологија за синтезу реактора заснована на концептима интензификације процеса и примени различитих оптимизационих техника (Reactor Synthesis Based on Process Intensification Concepts and Application of Optimization Methods – ReSyPIO). У поглављу Увод – Мотивација и циљеви, формиране су хипотезе на којима почива ReSyPIO методологија и дата је мотивација за истраживање. ReSyPIO методологија је укратко представљена и описана кроз три узастопне етапе. Прва етапа уоквирава све присутне фазе и феномене у реактору унутар функционалних градивних јединица, названих модули. Модули представљају резултат концептуалног приказа анализираног система. У другој етапи, модули се по потреби могу даље поделити у сегменте и међусобно повезати, креирајући суперструктуру реактора. Суперструктура је математички описана за све режиме рада реактора од интереса. У последњој етапи ReSyPIO методологије, оптимална структура, услови и режим рада реактора су одређени применом ригорозне оптимизације. Све три етапе ReSyPIO методологије имају повратни ток, што значи да уколико анализа води ка непрактичним, нефункционалним или неефикасним решењима, модификација математичког модела, суперструктуре и/или модула је могућа. Циљ примене ReSyPIO методологије је да се концептуалним и нумеричким приступом дође до оптималне препоруке за структуру реактора, оперативне услове и режим рада, која би била почетна претпоставка у будућем дизајну уређаја. Преглед литературе даје опис и приказ свих истраживања од интереса, из области Интензификације процеса и Теорије и анализе процесних система. Наглашени су различити приступи и студије присутне у истраживачкојзаједници, а њихови елементи упоређени са представљеном ReSyPIO методологијом са акцентом на предностима и научном доприносу. У овом поглављу је дат и низ добро истражених аналитичких и нумеричких приступа који би могли да буду коришћени у оквиру ReSyPIO методологије и олакшају њену примену. У поглављу Опис ReSyPIO методологије, је детаљно објашњена синтеза реактора заснована на концептима интензификације процеса и оптимизацији суперструктуре. Прво је дата процедура за графичку и концептуалну репрезентацију система, преко главних градивних јединица, феноменолошких модула. Потом је објашњено како се креира суперструктура реактора. На крају је дат уопштен поступак за математички опис суперструктуре преко скупова једначина материјалног и енергетског биланса, чији број зависи од броја присутних фаза и компонената у систему. ReSyPIO методологија је први пут примењена на случају две генеричке паралелне реакције у поглављу под називом Примена ReSyPIO методологије на случају генеричке реакције. Овај случај одговара реакцијама које се могу наћи у индустрији финих хемикалија. Реакције су ендотермне и споре, при чему је кинетички фаворизовано креирање нежељеног производа. Након примене ReSyPIO методологије, добијена је оптимална структура реактора која се састоји од сегментисаног модула са 17 улаза за извор топлоте и реактант који се дозира. Предложено је да реактор ради континуално, у стационарном режиму рада, јер би динамички режим рада резултовао недовољним повећањем ефикасности реактора..

A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems.

We have developed a new algorithm which merges discrete stochastic simulation, using the spatial stochastic simulation algorithm (sSSA), with the particle based fluid dynamics simulation framework of smoothed dissipative particle dynamics (SDPD). This hybrid algorithm enables discrete stochastic simulation of spatially resolved chemically reacting systems on a mesh-free dynamic domain with a Lagrangian frame of reference. SDPD combines two popular mesoscopic techniques: smoothed particle hydrodynamics and dissipative particle dynamics (DPD), linking the macroscopic and mesoscopic hydrodynamics effects of these two methods. We have implemented discrete stochastic simulation using the reaction-diffusion master equations (RDME) formalism, and deterministic reaction-diffusion equations based on the SDPD method. We validate the new method by comparing our results to four canonical models, and demonstrate the versatility of our method by simulating a flow containing a chemical gradient past a yeast cell in a microfluidics chamber

A hybrid smoothed dissipative particle dynamics (SDPD) spatial stochastic simulation algorithm (sSSA) for advection-diffusion-reaction problems.

We have developed a new algorithm which merges discrete stochastic simulation, using the spatial stochastic simulation algorithm (sSSA), with the particle based fluid dynamics simulation framework of smoothed dissipative particle dynamics (SDPD). This hybrid algorithm enables discrete stochastic simulation of spatially resolved chemically reacting systems on a mesh-free dynamic domain with a Lagrangian frame of reference. SDPD combines two popular mesoscopic techniques: smoothed particle hydrodynamics and dissipative particle dynamics (DPD), linking the macroscopic and mesoscopic hydrodynamics effects of these two methods. We have implemented discrete stochastic simulation using the reaction-diffusion master equations (RDME) formalism, and deterministic reaction-diffusion equations based on the SDPD method. We validate the new method by comparing our results to four canonical models, and demonstrate the versatility of our method by simulating a flow containing a chemical gradient past a yeast cell in a microfluidics chamber