Investigating the solid-state properties of the Earth’s core and mantle presents a formidable challenge due to the extreme conditions that prevail in these areas. Although we can achieve high pressures using a variety of static and dynamic compression techniques, it is still unfeasible to comprehensively sample the entire pressure-temperature (𝑃-𝑇) domain for materials. Therefore, computational methodologies have evolved as a crucial instrument for examining material properties under increased pressures and temperatures. These techniques have demonstrated their efficacy in navigating the phase space, thereby contributing significantly to the understanding of the intrinsic behavior of materials within the Earth’s interior. In this work, we present 𝚎𝚡𝚙𝚛𝚎𝚜𝚜, a comprehensive suite of simulation tools designed for conducting 𝘢𝘣 𝘪𝘯𝘪𝘵𝘪𝘰 calculations within the realm of the physical sciences. These tools are specifically engineered to streamline the associated data processing tasks, and they leverage the capabilities of the Julia programming language. At the core of this toolset lies a versatile, high-throughput, and user-friendly workflow framework. This framework is capable of automating a wide range of 𝘢𝘣 𝘪𝘯𝘪𝘵𝘪𝘰 calculations. By addressing the limitations encountered with existing libraries, 𝚎𝚡𝚙𝚛𝚎𝚜𝚜 simplifies intricate workflows, offers a software-agnostic interface, and ensures modularity—all of which are pivotal features within this domain. In addition to the workflow, we have developed a diverse set of software packages tailored to tackle the challenges inherent in data manipulation for 𝘢𝘣 𝘪𝘯𝘪𝘵𝘪𝘰 calculations. These packages encompass a wide spectrum of functionalities, including crystal symmetry search, conversion of units and reference frames, data visualization, parsing and generation of files, estimation of computing resources, and database storage, among other capabilities. We proceed to showcase the effectiveness of express across a diverse spectrum of mineral materials. For each substance, we conducted calculations of their thermodynamic properties using the quasi-harmonic approximation (QHA). This method was executed with the assistance of a Python package called 𝚚𝚑𝚊, which we developed specifically for multi-configuration quasi-harmonic approximation computations. In pursuit of our objective, we employ three distinct sets of exchange-correlation functionals: the local-density approximation (LDA), the Perdew–Burke–Ernzerhof generalized gradient approximation (PBE-GGA), and the PBE functional revised for solids (PBEsol). Subsequently, we compared these results with other calculations and experimental data, thereby elucidating the varying suitability of these functionals. Notably, the LDA functional, when integrated with thermal effects, exhibited exceptional overall performance. This observation implies that numerous studies that favored GGA functionals but solely relied on static DFT outcomes may have inadvertently incorporated erroneous material characteristics into their research.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Call number: LD2668 .T4 1984 J35 / Master of Science

Call number: LD2668 .T4 1986 B368 / Master of Science / Computing and Information Sciences

Thesis (MSc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: In this thesis we consider the problem of building a dense and consistent map of a mobile robot’s environment that is updated as the robot moves. Such maps are vital for safe and collision-free navigation. Measurements obtained from a range sensor mounted on the robot provide information on the structure of the environment, but are typically corrupted by noise. These measurements are also relative to the robot’s unknown pose (location and orientation) and, in order to combine them into a world-centric map, pose estimation is necessary at every time step. A SLAM system can be used for this task. However, since landmark measurements and robot motion are inherently noisy, the pose estimates are typically characterized by uncertainty. When building a map it is essential to deal with the uncertainties in range measurements and pose estimates in a principled manner to avoid overconfidence in the map. A literature review of robotic mapping algorithms reveals that the occupancy grid mapping algorithm is well suited for our goal. This algorithm divides the area to be mapped into a regular lattice of cells (squares for 2D maps or cubes for 3D maps) and maintains an occupancy probability for each cell. Although an inverse sensor model is often employed to incorporate measurement uncertainty into such a map, many authors merely state or depict their sensor models. We derive our model analytically and discuss ways to tailor it for sensor-specific uncertainty. One of the shortcomings of the original occupancy grid algorithm is its inability to convey uncertainty in the robot’s pose to the map. We address this problem by altering the occupancy grid update equation to include weighted samples from the pose uncertainty distribution (provided by the SLAM system). The occupancy grid algorithm has been criticized for its high memory requirements. Techniques have been proposed to represent the map as a region tree, allowing cells to have different sizes depending on the information received for them. Such an approach necessitates a set of rules for determining when a cell should be split (for higher resolution in a local region) and when groups of cells should be merged (for lower resolution). We identify some inconsistencies that can arise from existing rules, and adapt those rules so that such errors are avoided. We test our proposed adaptive occupancy grid algorithm, that incorporates both measurement and pose uncertainty, on simulated and real-world data. The results indicate that these uncertainties are included effectively, to provide a more informative map, without a loss in accuracy. Furthermore, our adaptive maps need far fewer cells than their regular counterparts, and our new set of rules for deciding when to split or merge cells significantly improves the ability of the adaptive grid map to mimic its regular counterpart. / AFRIKAANSE OPSOMMING: In hierdie tesis beskou ons die probleem om ’n digte en konsekwente kaart van ’n mobiele robot se omgewing te bou, wat opgedateer word soos die robot beweeg. Sulke kaarte is van kardinale belang vir veilige, botsingvrye navigasie. Metings verkry vanaf ’n sensor wat op die robot gemonteer is, verskaf inligting rakende die struktuur van die omgewing, maar word tipies deur ruis vervorm. Hierdie metings is ook relatief tot die robot se onbekende postuur (posisie en oriëntasie) en, om hulle saam te voeg in ’n wêreldsentriese kaart, is postuurafskatting nodig op elke tydstap. ’n SLAM stelsel kan vir hierdie doeleinde gebruik word. Aangesien landmerkmetings en die beweging van die robot inherent ruiserig is, word die postuurskattings gekarakteriseer deur onsekerheid. Met die bou van ’n kaart moet hierdie onsekerhede in afstandmetings en postuurskattings op ’n beginselvaste manier hanteer word om te verhoed dat te veel vertroue in die kaart geplaas word. ’n Literatuurstudie van karteringsalgoritmes openbaar die besettingsroosteralgoritme as geskik vir ons doel. Die algoritme verdeel die gebied wat gekarteer moet word in ’n reëlmatige rooster van selle (vierkante vir 2D kaarte of kubusse vir 3D kaarte) en onderhou ’n besettingswaarskynlikheid vir elke sel. Alhoewel ’n inverse sensormodel tipies gebruik word om metingsonsekerheid in so ’n kaart te inkorporeer, noem of wys baie outeurs slegs hulle model. Ons herlei ons model analities en beskryf maniere om sensorspesifieke metingsonsekerheid daarby in te sluit. Een van die tekortkominge van die besettingsroosteralgoritme is sy onvermoë om onsekerheid in die postuur van die robot na die kaart oor te dra. Ons spreek hierdie probleem aan deur die opdateringsvergelyking van die oorspronklike besettingsroosteralgoritme aan te pas, om geweegde monsters van die postuuronsekerheidsverdeling (verskaf deur die SLAM stelsel) in te sluit. Die besettingsroosteralgoritme word soms gekritiseer vir sy hoë verbruik van geheue. Tegnieke is voorgestel om die kaart as ’n gebiedsboom voor te stel, wat selle toelaat om verskillende groottes te hê, afhangende van die inligting wat vir hulle verkry is. So ’n benadering noodsaak ’n stel reëls wat spesifiseer wanneer ’n sel verdeel (vir ’n hoër resolusie in ’n plaaslike gebied) en wanneer ’n groep selle saamgevoeg (vir ’n laer resolusie) word. Ons identifiseer teenstrydighede wat kan voorkom as die huidige reëls gevolg word, en pas hierdie reëls aan sodat sulke foute vermy word. Ons toets ons voorgestelde aanpasbare besettingsroosteralgoritme, wat beide metings- en postuuronsekerheid insluit, op gesimuleerde en werklike data. Die resultate dui daarop dat hierdie onsekerhede op ’n effektiewe wyse na die kaart oorgedra word sonder om akkuraatheid prys te gee. Wat meer is, ons aanpasbare kaarte benodig heelwat minder selle as hul reëlmatige eweknieë. Ons nuwe stel reëls om te besluit wanneer selle verdeel of saamgevoeg word, veroorsaak ook ’n merkwaardige verbetering in die vermoë van die aanpasbare roosterkaart om sy reëlmatige eweknie na te boots.

published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

published_or_final_version / Computer Science / Master / Master of Philosophy

A methodology for the automatic translation of a Hardware Description Language (HDL) formulation of a VLSI system to a structured array-type of target realization is the subject of this investigation. A particular combination of input HDL and target technology has been implemented as part of the exercise, and a detailed evaluation of the result is presented. The HDL used in the study is AHPL, a synchronous clock-mode language which accepts the description of the hardware at Register Transfer Level. The target technology selected is Storage Logic Array (SLA), an evolution of PLA concept. Use of the SLA has a distinct advantage, notably in the ability to sidestep the interconnection routing problem, an expensive and time-consuming process in normal IC design. Over the past years, an enormous amount of effort has gone into generation of layout from an interconnection list. This conventional approach seems to complicate the placement and routing processes in later stages. In this research project the major emphasis has therefore been on extracting relevant global information from the higher-level description to guide the subsequent placement and routing algorithms. This effectively generates the lower-level layout directly from higher-level description. A special version of AHPL compiler (stage 3) has been developed as part of the project. The SLA data structure formats and the implementation of the Data and Control Sections of the target are described in detail. Also the evaluation and possibilities for future research are discussed.

No description available.

Operatorless Prolog text is LL(1) in nature and any standard LL parser generator tool can be used to parse it. However, the Prolog text that conforms to the ISO Prolog standard allows the definition of dynamic operators. Since Prolog operators can be defined at run-time, operator symbols are not present in the grammar rules of the language. Unless the parser generator allows for some flexibility in the specification of the grammar rules, it is very difficult to generate a parser for such text. In this thesis we discuss the existing parsing methods and their modified versions to parse languages with dynamic operator capabilities. Implementation details of a parser using Javacc as a parser generator tool to parse standard Prolog text is provided. The output of the parser is an “Abstract Syntax Tree” that reflects the correct precedence and associativity rules among the various operators (static and dynamic) of the language. Empirical results are provided that show that a Prolog parser that is generated by the parser generator like Javacc is comparable in efficiency to a hand-coded parser.