Transient Mobilisation of Pipe-Wall Adhered Material in Drinking Water Distribution Systems

Discolouration, an aesthetic indicator of drinking water quality, affects approximately 6.7 million customers annually in the UK and is perceived to mask other water quality failures. Existing management techniques cannot explain all of these discolouration failures. Therefore, understanding the processes and forces that lead to discolouration is crucial. Material associated with discolouration is mobilised from the pipe wall when its adherence strength is exceeded by imposed hydraulic forces. Transient events generate significant dynamic forces, yet, there is currently little conclusive evidence exploring their influence on mobilisation of material. This study aims to determine, for the first time, if transient forces can mobilise of material adhered to the pipe-wall, which cannot be mobilised by steady state flows at the same initial or final conditions. An innovative, rigorous laboratory experiment was designed to test this aim. Replicated adhered material was created using magnetic particles inside the pipe and an electromagnet external to the pipe, so that controlled current through the electromagnet quantified adherence force experienced by the magnetic particles. Hydraulic steady state and transient tests, for a range of flow rate and pressure conditions, were conducted to determine the current at which mobilisation occurred. A key contribution of this research was the confirmation that valve closing and valve opening transients cause mobilisation of adhered material, where steady state cannot. This is substantial finding, particularly for valve closing transients as the steady state force reduces during the valve movement. Mobilisation must be due to the dynamic forces generated by the transient. An observationally driven analysis led to development of a function to capture the magnitude of the hydraulic force generated during transients. The one dimensional function was termed the ‘Peak Dynamic Force’ and begins to quantify transient induced forces that lead to mobilisation of pipe-wall adhered material. The work presented within this thesis is unique in that it consistently isolated transient forces and quantified their mobilisation ability. This dynamic ability has theoretical and practical implications, and could ultimately lead to the development of effective management strategies for improving drinking water quality

Product-form in G-networks

The introduction of the class of queueing networks called G-networks by Gelenbe has been a breakthrough in the field of stochastic modeling since it has largely expanded the class of models which are analytically or numerically tractable. From a theoretical point of view, the introduction of the G-networks has lead to very important considerations: first, a product-form queueing network may have non-linear traffic equations; secondly, we can have a product-form equilibrium distribution even if the customer routing is defined in such a way that more than two queues can change their states at the same time epoch. In this work, we review some of the classes of product-forms introduced for the analysis of the G-networks with special attention to these two aspects. We propose a methodology that, coherently with the product-form result, allows for a modular analysis of the G-queues to derive the equilibrium distribution of the network

Methodology for the Accelerated Reliability Analysis and Prognosis of Underground Cables based on FPGA

Dependable electrical power distribution systems demand high reliability levels that cause increased maintenance costs to the utilities. Often, the extra costs are the result of unnecessary maintenance procedures, which can be avoided by monitoring the equipment and predicting the future system evolution by means of statistical methods (prognostics). The present thesis aims at designing accurate methods for predicting the degradation of high and medium voltage underground Cross-Linked Polyethylene (XLPE) cables within an electrical power distribution grid, and predicting their remaining useful life, in order inform maintenance procedures. However, electric power distribution grids are large, components interact with each other, and they degrade with time and use. Solving the statistics of the predictive models of the power grids currently requires long numerical simulations that demand large computational resources and long simulation times even when using advanced parallel architectures. Often, approximate models are used in order to reduce the simulation time and the required resources. In this context, Field Programmable Gate Arrays (FPGAs) can be employed to accelerate the simulation of these stochastic processes. However, the adaptation of the physicsbased degradation models of underground cables for FPGA simulation can be complex. Accordingly, this thesis proposes an FPGA-based framework for the on-line monitoring and prognosis of underground cables based on an electro-thermal degradation model that is adapted for its accelerated simulation in the programmable logic of an FPGA.Energia elektrikoaren banaketa-sare konfidagarriek fidagarritasun maila altuak eskatzen dituzte, eta honek beraien mantenketa kostuen igoera dakar. Kostu hauen arrazoia beraien bizitzan goizegi egiten diren mantenketa prozesuei dagokie askotan, eta hauek eragoztea posible da, ekipamenduaren monitorizazioa eginez eta sistemaren etorkizuneko eboluzioa aurrez estimatuz (prognosia). Tesi honen helburua lurpeko tentsio altu eta ertaineko Cross-Linked Polyethylene (XLPE) kable sistemen eboluzioa eta geratzen zaien bizitza aurreikusiko duten metodo egokiak definitzea izango da, banaketa-sare elektriko baten barruan, ondoren mantenketa prozesu optimo bat ahalbidetuko duena. Hala ere, sistema hauek oso jokaera dinamikoa daukate. Konponente ezberdinek beraien artean elkar eragiten dute eta degradatu egiten dira denboran eta erabileraren ondorioz. Estatistika hauen soluzio analitikoa lortzea ezinezkoa da gaur egun, eta errekurtso asko eskatzen dituen simulazio luzeak behar ditu zenbakizko erantzun bat lortzeko, arkitektura paralelo aurreratuak erabili arren. Field Programmable Gate Array (FPGA)k prozesu estokastiko hauen simulazioa azkartzeko erabil daitezke, baina lurpeko kableen degradazio prozesuen modelo fisikoak FPGA exekuziorako egokitzea konplexua izan daiteke. Beraz, tesi honek FPGA baten logika programagarrian azeleratu ahal izateko egokitua izan den degradazio elektrotermiko modelo baten oinarritutako monitorizazio eta prognosi metodologia bat proposatzen du.Las redes de distribución de energía eléctrica confiables requieren de altos niveles de fiabilidad, que causan un mayor coste de mantenimiento a las empresas distribuidoras. Frecuentemente los costes adicionales son el resultado de procedimientos de mantenimiento innecesarios, que se pueden evitar por medio de la monitorización de los equipos y la predicción de la evolución futura del sistema, por medio de métodos estadísticos (prognosis). La presente tesis pretende desarrollar métodos adecuados para la predicción de la degradación futura de cables de alta y media tensión Cross-Linked Polyethylene (XLPE) soterrados, dentro de una red de distribución eléctrica, y predecir su tiempo de vida restante, para definir una secuencia de mantenimiento óptima. Sin embargo, las redes de distribución eléctrica son grandes, y compuestas por componentes que interactúan entre sí y se degradan con el tiempo y el uso. En la actualidad, resolver estas estadísticas predictivas requieren grandes simulaciones numéricas que requieren de grandes recursos computacionales y largos tiempos de simulación, incluso utilizando arquitecturas paralelas avanzadas. Las Field Programmable Gate Array (FPGA) pueden ser utilizadas para acelerar las simulaciones de estos procesos estocásticos, pero la adaptación de los modelos físicos de degradación de cables soterrados para su simulación en una FPGA puede ser complejo. Así, esta tesis propone el desarrollo de una metodología de monitorización y prognosis cables soterrados, basado en un modelo de degradación electro-térmico que está adaptado para su simulación acelerada en la lógica programable de una FPGA

Self-adaptivity of applications on network on chip multiprocessors: the case of fault-tolerant Kahn process networks

Technology scaling accompanied with higher operating frequencies and the ability to integrate more functionality in the same chip has been the driving force behind delivering higher performance computing systems at lower costs. Embedded computing systems, which have been riding the same wave of success, have evolved into complex architectures encompassing a high number of cores interconnected by an on-chip network (usually identified as Multiprocessor System-on-Chip). However these trends are hindered by issues that arise as technology scaling continues towards deep submicron scales. Firstly, growing complexity of these systems and the variability introduced by process technologies make it ever harder to perform a thorough optimization of the system at design time. Secondly, designers are faced with a reliability wall that emerges as age-related degradation reduces the lifetime of transistors, and as the probability of defects escaping post-manufacturing testing is increased. In this thesis, we take on these challenges within the context of streaming applications running in network-on-chip based parallel (not necessarily homogeneous) systems-on-chip that adopt the no-remote memory access model. In particular, this thesis tackles two main problems: (1) fault-aware online task remapping, (2) application-level self-adaptation for quality management. For the former, by viewing fault tolerance as a self-adaptation aspect, we adopt a cross-layer approach that aims at graceful performance degradation by addressing permanent faults in processing elements mostly at system-level, in particular by exploiting redundancy available in multi-core platforms. We propose an optimal solution based on an integer linear programming formulation (suitable for design time adoption) as well as heuristic-based solutions to be used at run-time. We assess the impact of our approach on the lifetime reliability. We propose two recovery schemes based on a checkpoint-and-rollback and a rollforward technique. For the latter, we propose two variants of a monitor-controller- adapter loop that adapts application-level parameters to meet performance goals. We demonstrate not only that fault tolerance and self-adaptivity can be achieved in embedded platforms, but also that it can be done without incurring large overheads. In addressing these problems, we present techniques which have been realized (depending on their characteristics) in the form of a design tool, a run-time library or a hardware core to be added to the basic architecture

by integrating deep learning, mechanistic model and field observations

학위논문(박사) -- 서울대학교대학원 : 농업생명과학대학 협동과정 농림기상학, 2022. 8. Youngryel Ryu.Rice (Oryza sativa) is a vital cereal crop that feeds more than 50% of the world population. However, the traditional anaerobic management leads rice production to consume ~40% of the irrigation water and emit ~10% of the global anthropogenic methane. A new paradigm for sustainable rice farming is urgently required amid challenges from increasing food demand, water scarcity, and reducing greenhouse gases emissions. Rice plants transpire considerable water overnight. Saving nighttime water loss is desirable but first need to understand the underlying mechanism of nocturnal stomatal opening. Apart from the night, optimizing daytime management is pivotal for designing an environmentally sustainable rice farming system. In a long-term strategy, detailed and reliable crop type map is compulsory to upscale new leaf level findings and site level methods to regional or global scale. Therefore, in this dissertation, we improved mechanistic understanding of nocturnal stomatal conductance in rice plants (Chapter II); provided an interdisciplinary and heuristic approach for designing an environmentally sustainable rice farming system with a case study in South Korea (Chapter III); and developed a new crop type referencing method by mining off-the-shelf Google Street View images to map crop types (Chapter IV). In chapter II, we proposed a “coordinated leaf trait” hypothesis to explain the ecological mechanism of nocturnal stomatal conductance (gsn) in rice. We conducted an open-field experiment by applying drought, nutrient deficiency, and the combined drought-nutrient deficiency stress. We found that gsn was neither strongly reduced by drought nor consistently increased by nutrient deficiency. With abiotic stress as a random effect, gsn was strongly positively correlated with nocturnal respiration (Rn). Notably, gsn primed early morning photosynthesis, as follows: Rn (↑) → gsn (↑) → gsd (daytime stomatal conductance) (↑) → A (assimilation) (↑). This photosynthesis priming effect diminished after mid-morning. Leaves were cooled by gsn as follows: gsn (↑) → E (transpiration) (↑) → Tleaf (leaf temperature) (↓). However, our results clearly suggest that evaporative cooling did not reduce Rn cost. Our results indicate that gsn is more closely related to carbon respiration and assimilation than water and nutrient availability, and that leaf trait coordination (Rn − gsn − gsd − A) is likely the primary mechanism controlling gsn. In chapter III, we aimed to increase current crop yield, reduce irrigation water consumption, and tackle the dilemma to simultaneously reducing CH4 and N2O emissions in a flooded rice production system. By proposing a heuristic and holistic method, we optimized farm management beyond previous most emphasized irrigation regimes while also exploring niches from other pivotal options regarding sowing window, fertilization rate, tillage depth, and their interactions. Specifically, we calibrated and validated the process-based DNDC model with five years of eddy covariance observations. The DNDC model later was integrated with the non-dominated sorting genetic algorithm (NSGA-III) to solve the multi-objective optimization problem. We found that the optimized management would maintain or even increase current crop yield to its potential (~10 t/ha) while reducing more than 50% irrigation demand and GHGs (CH4 & N2O) emissions. Our results indicate that earlier sowing window and improvements on irrigation practice together would be pivotal to maximizing crop yield while sustaining environmental benefits. We found that the optimal fraction of non-flooded days was around 54% of growing season length and its optimal temporal distributions were primarily in vegetative stages. Our study shows that the present farm yield (8.3-8.9 t/ha) in study site not only has not achieved its potential level but also comes at a great environmental cost to water resources (604-810 mm/yr) and GHGs emissions (CH4: 186-220 kg C/ha/yr; N2O: 0.3-1.6 kg C/ha/yr). Furthermore, this simple method could further be applied to evaluate the environmental sustainability of a farming system under various climate and local conditions and to guide policymakers and farming practices with comprehensive solutions. In chapter IV, we apply a convolutional neural network (CNN) model to explore the efficacy of automatic ground truthing via Google Street View (GSV) images in two distinct farming regions: Illinois and the Central Valley in California. Ground reference data are an essential prerequisite for supervised crop mapping. The lack of a low-cost and efficient ground referencing method results in pervasively limited reference data and hinders crop classification. In this study, we demonstrate the feasibility and reliability of our new ground referencing technique by performing pixel-based crop mapping at the state level using the cloud-based Google Earth Engine platform. The mapping results are evaluated using the United States Department of Agriculture (USDA) crop data layer (CDL) products. From ~130,000 GSV images, the CNN model identified ~9,400 target crop images. These images are well classified into crop types, including alfalfa, almond, corn, cotton, grape, rice, soybean, and pistachio. The overall GSV image classification accuracy is 92% for the Central Valley and 97% for Illinois. Subsequently, we shifted the image geographical coordinates 2–3 times in a certain direction to produce 31,829 crop reference points: 17,358 in Illinois, and 14,471 in the Central Valley. Evaluation of the mapping results with CDL products revealed satisfactory coherence. GSV-derived mapping results capture the general pattern of crop type distributions for 2011–2019. The overall agreement between CDL products and our mapping results is indicated by R2 values of 0.44–0.99 for the Central Valley and 0.81–0.98 for Illinois. To show the applicational value of the proposed method in other countries, we further mapped rice paddy (2014–2018) in South Korea which yielded fairly well outcomes (R2=0.91). These results indicate that GSV images used with a deep learning model offer an efficient and cost-effective alternative method for ground referencing, in many regions of the world.쌀(오리자 사티바)은 세계 인구의 50% 이상을 먹여 살리는 중요한 곡물 작물이다. 그러나 전통적인 혐기성 관리는 쌀 생산으로 관개수의 40%를 소비하고 전 세계 인공 메탄의 10%를 배출한다. 식량 수요 증가, 물 부족, 온실가스 배출 감소 등의 과제 속에서 지속 가능한 벼농사를 위한 새로운 패러다임이 시급하다. 벼는 하룻밤 사이에 상당한 양의 물을 내뿜는다. 야간 수분 손실을 줄이는 것은 바람직하지만, 먼저 야간 기공 개방의 기본 메커니즘을 이해할 필요가 있다. 야간과 별도로 주간 경영의 최적화는 환경적으로 지속 가능한 벼농사 시스템을 설계하는 데 매우 중요하다. 장기 전략에서, 새로운 잎 수준 발견과 현장 수준 방법을 지역적 또는 전역적 규모로 상향 조정하려면 상세하고 신뢰할 수 있는 작물 유형 맵이 필수적이다. 따라서, 본 논문에서 우리는 벼농사의 야간 기공 전도도에 대한 기계적 이해를 향상시켰다(제2장). 환경적으로 지속 가능한 벼농사 시스템을 설계하기 위한 학제 간 및 휴리스틱 접근법 제공(제3장). 그리고 새로운 작물 유형 참조 방법을 개발했다. 기성품인 Google Street View 이미지를 마이닝하여 자르기 유형을 매핑합니다. 2장에서 우리는 벼의 야행성 기공 전도도(gsn)의 생태학적 메커니즘을 설명하기 위해 "협동된 잎 형질" 가설을 제안했습니다. 가뭄, 영양 결핍 및 가뭄-영양소 결핍 복합 스트레스를 적용하여 노지 실험을 수행했습니다. 우리는 gsn이 가뭄에 의해 크게 감소하지도 않고 영양 결핍에 의해 지속적으로 증가하지도 않는다는 것을 발견했습니다. 무생물적 스트레스를 무작위 효과로 사용하여 gsn은 야간 호흡(Rn)과 강한 양의 상관관계를 보였습니다. 특히, gsn은 Rn(↑) → gsn(↑) → gsd(주간 기공 전도도)(↑) → A(동화)(↑)와 같이 이른 아침 광합성을 프라이밍했습니다. 이 광합성 프라이밍 효과는 오전 중반 이후에 감소했습니다. 잎은 gsn에 의해 다음과 같이 냉각되었습니다: gsn(↑) → E(증산)(↑) → Tleaf(잎 온도)(↓). 그러나 우리의 결과는 증발 냉각이 Rn 비용을 감소시키지 않았다는 것을 분명히 시사합니다. 우리의 결과는 gsn이 물 및 영양소 가용성보다 탄소 호흡 및 동화와 더 밀접하게 관련되어 있으며 잎 형질 조정(Rn - gsn - gsd - A)이 gsn을 제어하는 주요 메커니즘일 가능성이 있음을 나타냅니다. 제3장에서 우리는 현재의 작물 수확량을 늘리고 관개 용수 소비를 줄이며 침수된 쌀 생산 시스템에서 CH4와 N2O 배출량을 동시에 줄이는 딜레마를 해결하는 것을 목표로 했다. 휴리스틱하고 전체론적 방법을 제안함으로써, 우리는 이전에 가장 강조되었던 관개 체제를 넘어 농장 관리를 최적화함과 동시에 파종 창, 수정률, 경작 깊이 및 이들의 상호 작용과 관련된 다른 중추적 옵션의 틈새를 탐색했다. 구체적으로, 우리는 5년간의 와류 공분산 관찰로 프로세스 기반 DNDC 모델을 교정하고 검증했다. DNDC 모델은 나중에 다중 객관적 최적화 문제를 해결하기 위해 비지배적 정렬 유전 알고리듬(NSGA-III)과 통합되었다. 우리는 최적화된 관리를 통해 50% 이상의 관개 수요와 GHG(CH4 & N2O) 배출량을 줄이면서 현재 농작물 수확량을 잠재력(~10t/ha)까지 유지하거나 증가시킬 수 있다는 것을 발견했습니다. 우리의 결과는 더 이른 파종 기간과 관개 관개 관행의 개선이 환경적 이익을 유지하면서 농작물 수확량을 최대화하는 데 중추적일 것이라는 것을 보여준다. 우리는 홍수 없는 날의 최적 부분이 성장기 길이의 약 54%였고 최적의 시간 분포는 주로 식물 단계에 있다는 것을 발견했다. 우리의 연구는 연구 현장의 현재 농장 수확량(8.3-8.9 t/ha)이 잠재적 수준을 달성했을 뿐만 아니라 수자원(604-810 mm/yr)과 GHGs 배출(CH4: 186-220 kg C/ha/yr; N2O: 0.3-1.6 kg C/ha/yr)에 막대한 환경 비용을 초래한다는 것을 보여준다. 또한, 이 간단한 방법은 다양한 기후 및 지역 조건 하에서 농업 시스템의 환경 지속 가능성을 평가하고 정책 입안자와 농업 관행을 포괄적인 해결책으로 안내하는 데 추가로 적용될 수 있다. 제4장에서는 컨볼루션 신경망(CNN) 모델을 적용하여 두 개의 구별되는 농업 지역에서 구글 스트리트 뷰(GSV) 이미지를 통해 자동 지상 트러싱의 효과를 탐구한다. 일리노이와 캘리포니아의 센트럴 밸리. 지상 참조 데이터는 감독된 작물 매핑을 위한 필수 전제 조건이다. 저렴하고 효율적인 지상 참조 방법이 없기 때문에 참조 데이터가 광범위하게 제한되고 작물 분류를 방해한다. 본 연구에서는 클라우드 기반 Google 어스 엔진 플랫폼을 사용하여 상태 수준에서 픽셀 기반 크롭 매핑을 수행하여 새로운 지상 참조 기술의 실현 가능성과 신뢰성을 입증한다. 매핑 결과는 미국 농무부(USDA) 작물 데이터층(CDL) 제품을 사용하여 평가된다. 약 130,000개의 GSV 이미지에서 CNN 모델은 약 9,400개의 목표 크롭 이미지를 식별했다. 이 이미지들은 알팔파, 아몬드, 옥수수, 면화, 포도, 쌀, 콩, 피스타치오 등의 작물 유형으로 잘 분류된다. 전체 GSV 이미지 분류 정확도는 센트럴 밸리의 경우 92%, 일리노이 주의 경우 97%이다. 그 후 이미지 지리적 좌표를 특정 방향으로 2~3회 이동하여 31,829개의 크롭 기준점을 생성했다. 즉, 일리노이에서 17,358개, 센트럴 밸리에서 14,471개였다. CDL 제품으로 매핑 결과를 평가한 결과 만족스러운 일관성이 나타났다. GSV에서 파생된 매핑 결과는 2011-2019년 작물 유형 분포의 일반적인 패턴을 포착한다. CDL 제품과 우리의 매핑 결과 사이의 전체 합치는 센트럴 밸리의 경우 0.44–0.99의 R2 값과 일리노이 주의 경우 0.81–0.98의 R2 값으로 표시된다. 제안된 방법의 다른 국가에서 적용 가치를 보여주기 위해, 꽤 좋은 결과를 얻은 한국의 논(2014–2018)을 추가로 매핑했다(R2=0.91). 이러한 결과는 딥 러닝 모델과 함께 사용되는 GSV 이미지가 세계의 많은 지역에서 지상 참조를 위한 효율적이고 비용 효율적인 대체 방법을 제공한다는 것을 나타낸다.1. Abstract 3 LIST OF FIGURES 9 LIST OF TABLES 13 ACKNOWLEDGEMENTS 14 Chapter I. Introduction 15 1.1. Study Background 15 1.2. Purpose of Research 15 Chapter II. Nocturnal stomatal conductance in rice: a coordinating bridge between prior respiration and photosynthesis next dawn 17 Abstract 17 1. Introduction 18 2. Materials and Methods 22 2.1 Plants and growth conditions 22 2.2 Leaf physiological traits 22 2.3 Rapid A/Ci response curves 24 2.4 Stomatal anatomy measurements 24 2.5 Statistical analyses 24 3. Results 25 3.1 Effects of abiotic stress on leaf traits 25 3.2 Nighttime leaf physiological traits 26 3.3 Significant priming effects of gsn on early morning photosynthesis (~5:00 – 7:00) 27 3.4 Path analyses only support the leaf trait coordination 28 3.5 Impacts of gsn on gsd and Amax under light-saturated conditions 29 3.6 Photosynthesis priming effects not detected after mid-morning (9:00) 31 4. Discussion 32 4.1 Abiotic stress results: Implications for different hypotheses 33 4.2 Enhanced carbon assimilation through coordinated regulation by gsn 34 4.3 Evaporative cooling: Passive thermoregulation via leaf trait coordination 36 References 37 Chapter III. Multi-objective optimization of crop yield, water consumption, and greenhouse gases emissions for sustainable rice production 42 Abstract 42 1. Introduction 43 2. Materials and methods 46 2.1 Study site 46 2.2 DNDC model 46 2.3 In situ data 47 2.4 Multi-objective optimization (MOO) algorithm 48 2.5 DNDC-NSGA-III integration and optimization 48 3. Results 50 3.1 DNDC model validation 50 3.2 The gaps between the current farming outcomes and optimized objectives 53 3.3 Approaching Pareto fronts through the heuristic and holistic management 55 3.4 The gaps between current farming practices to potential crop yield with optimal holistic management 56 4. Discussion 58 4.1 Could heuristic and holistic management increase current rice yield with less irrigation water? 58 4.2 Could heuristic and holistic management simultaneously reduce CH4 and N2O emissions? 59 4.3 Limitations and uncertainties 60 Reference 61 Chapter IV. Exploring Google Street View with Deep Learning for Crop Type Mapping 70 Abstract 70 1. Introduction 71 2. Materials and Methods 74 2.1 Study area 74 2.2 General methodology 75 2.3 Google Street View image collection 76 2.4 CNN model training and validation 77 2.5 Producing ground reference data and quality control 79 2.6 Mapping crop types 80 2.7 Mapping results evaluation 81 2.8 Additional test case 82 3. Results 83 3.1 GSV image classification 83 3.2 Producing ground reference data from classified GSV images 84 3.3 Mapping using the GSV derived ground reference 86 4. Discussion 96 4.1 Can we use GSV images to efficiently produce low-cost, sufficient, and reliable crop type ground reference data covering large areas? 96 4.2 Can we use GSV-derived reference data as “ground truth” to map crop types for large areas spanning many years? 97 Appendix 99 References 105 Chapter V. Conclusions 123 Supplementary Information Chapter II 125 Supplementary Information Chapter III 131 Supplementary Information Chapter IV 135 5. Abstract in Korean 138박

Hybrid DES-based Vehicular Network Simulator with Multichannel Operations

Vehicular Ad-hoc Network (VANET) is considered to be a viable technology for inter- vehicle communications for the purpose of improving road safety and efficiency. The En- hanced Distribution Channel Access (EDCA) mechanism and multichannel operations are introduced to ensure the Quality of Service (QoS). Therefore, it is necessary to create an accurate vehicular network simulator that guarantees the vehicular communications will work as described in the protocols. A comprehensive vehicular network simulator should consider the interaction between mobility models and network protocols. In this dissertation, a novel vehicular network simulation environment, VANET Toolbox, designed using discrete-event system (DES) is presented. The APP layer DES Module of the proposed simulator integrates vehicular mo- bility operations with message generation functions. The MAC layer DES module supports single channel and multichannel EDCA operations. The PHY layer DES module supports bit-level processing. Compared with packet-based simulator such as NS-3, the proposed PHY layer is more realistic and accurate. The EDCA scheme is evaluated and compared with the traditional Carrier-Sensing Mul- tiple Access (CSMA) scheme, with the simulations proving that data with different priorities can coexist in the same channel. The multichannel operation for the EDCA scheme is also analyzed in this dissertation. The multichannel switching operation and coordination may cause packet dropping or increased latency to the communication. The simulations show that with heavy network traffic, multichannel communication performs better than single channel communication. From the perspective of safety-related messages, the multichannel operation is able to isolate the interference from the non-safety messages in order to achieve a better packet delivery rate and latency. On the other hand, the non-safety messages can achieve high throughput with reasonable latency from multichannel communication under heavy load traffic scenario

Improving the efficiency of grid connected PV system for real operating conditions

This PhD thesis is focused on modelling and development of an improved Maximum Power Point Tracking (MPPT) designed for real operating conditions. Real operating conditions involve changing irradiance and temperature and also often partial shading of the array. It is also common for there to be temperature variation across the array, and also some dierences in the intrinsic quality and eciency of individual cells and modules. These eects combine to give a degree of mismatch between the cells and modules within the array that is time varying. Commercial inverters are not designed to deal with the resulting nonideal system IV curves, and thus can deliver poor MPPT performance that can degrade signicantly the overall eciency of power conversion. The novelty of this research is the development of a Maximum Power Point Tracking algorithm able to indentify accurately and rapidly the MPP under real operating conditions, and thus improve the system performance especially when the mismatch issues outlined above lead to multiple local maxima in the power output of the array (as a function of array voltage). To underpin the development of the new MPPT algorithm, a detailed model of the PV system was developed. This is built up from models of individual cells and modules so as to properly represent cell mismatch. This model has been tested and validated using real measured data from a test rig installed on the roof of James Weir Building of Strathclyde University. The test rig was equipped with comprehensive and appropriate instrumentation to measure both the ambient conditions and the PV performance. Over an extended period of monitoring a substantial amount of high quality detailed data was collected from the roof test rig, and this has been used to develop and rene an algorithm able to track the MPP highly eectively under time varying real outdoor operating conditions. The algorithm uses an Articial Neural Network (ANN) to predict the MPP in the case of partial shading and also any other operating conditions likely to be experienced; the algorithm includes additional code to assist the ANN in tracking the true maximum within a variable time step. It has been implemented on a modelled DC/DC converter to test dierent power conditions and also dierent types of modules with dierent Fill Factors. Finally, the control technique developed has been implemented in a real DC/DC converter but using an electronic PV array simulator rather than the outdoor system to provide more controlled operational condition

Experimental study of filling and emptying of a large-scale pipeline

The ¿lling with liquid of an initially empty pipeline and its counterpart, the draining of an initially liquid-¿lled pipeline, are of great interest due to the many practical applications. Several potential problems may occur, of which water-hammer and slug impact are the most important. To investigate the ¿lling and emptying processes, di¿erent mathematical models have been proposed, in which a common assumption is that the water column evolves with unchanged front and/or tail. This is a reasonable assumption for small-scale systems, particularly in cases with relatively high upstream pressure head and low downstream resistance. However, it is not clear whether this assumption is applicable to large-scale systems. This issue is of high importance for the development of air pockets and gravity currents in pipelines during ¿lling and draining processes. This study presents the experimental results of the ¿ow behaviour during the rapid ¿lling and emptying of a large-scale pipeline. The experimental apparatus was designed and built at Deltares, Delft, The Netherlands, as part of the EC Hydralab III project. Di¿erent from other laboratory studies, the scale of this experiment is close to the practical situation in many industrial plants. The test rig includes a variety of components (e.g. tanks, ¿ow meters, valves, pipes of di¿erent materials) and the operation procedure is rather complex. The ¿ow behaviour is measured by various instruments and hence a thorough hydrodynamic analysis is possible. All these features make the current study particularly useful as a test case for real ¿lling and draining situations. In the ¿lling of an initially empty pipeline, the focus was on the overall behaviour of the lengthening water column and the water-air interface evolution. In the emptying of an initially water-¿lled pipeline, together with the hydrodynamics of the shortening water column, the shape and behaviour of the water tail (air-water interface) was investigated. Thirteen di¿erent combinations of initial upstream driving air pressure and downstream valve resistance were tested. The in¿uence of these two factors on the out¿ow rate is clari¿ed. It was con¿rmed that both the in¿ow front in ¿lling and the out¿ow tail in emptying do not entirely ¿ll the pipe cross section. Shape changes occur at both the water-air and air-water interfaces. Although the ¿ow regime transition is a rather complex phenomenon, certain features of the transition pattern are observed and explained qualitatively and quantitatively

Exploring coordinated software and hardware support for hardware resource allocation

Multithreaded processors are now common in the industry as they offer high performance at a low cost. Traditionally, in such processors, the assignation of hardware resources between the multiple threads is done implicitly, by the hardware policies. However, a new class of multithreaded hardware allows the explicit allocation of resources to be controlled or biased by the software. Currently, there is little or no coordination between the allocation of resources done by the hardware and the prioritization of tasks done by the software.This thesis targets to narrow the gap between the software and the hardware, with respect to the hardware resource allocation, by proposing a new explicit resource allocation hardware mechanism and novel schedulers that use the currently available hardware resource allocation mechanisms.It approaches the problem in two different types of computing systems: on the high performance computing domain, we characterize the first processor to present a mechanism that allows the software to bias the allocation hardware resources, the IBM POWER5. In addition, we propose the use of hardware resource allocation as a way to balance high performance computing applications. Finally, we propose two new scheduling mechanisms that are able to transparently and successfully balance applications in real systems using the hardware resource allocation. On the soft real-time domain, we propose a hardware extension to the existing explicit resource allocation hardware and, in addition, two software schedulers that use the explicit allocation hardware to improve the schedulability of tasks in a soft real-time system.In this thesis, we demonstrate that system performance improves by making the software aware of the mechanisms to control the amount of resources given to each running thread. In particular, for the high performance computing domain, we show that it is possible to decrease the execution time of MPI applications biasing the hardware resource assignation between threads. In addition, we show that it is possible to decrease the number of missed deadlines when scheduling tasks in a soft real-time SMT system.Postprint (published version