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In the study, the effect rates of independent variables (cutting speed, feed rate, cutting depth and tool nose radius) on the dependent variables (surface roughness) used during turning of C45 manufacturing steel were investigated and optimum cutting parameters were determined. Turning experiments were performed according to the L27 orthogonal (Vertical) array of the response surface method (RSM). As independent variables 3 different cutting speeds (160 m/min, 260 m/min and 360 m/min), feed rate (0.05 mm/rpm, 0.18 mm/rpm and 0.31 mm/rpm), cutting depth (0.1 mm, 0.3 mm and 0.5 mm) and tool nose radius (0.4 mm, 0.8 mm and 1.2 mm) were used. As a result analysis of Variance, the effects of independent variables and the effects of interactions on dependent variables were examined. As a result, it was determined that the most effective independent variable on the dependent variable was the feed rate and tool nose radius, respectively, while the effect of cutting speed and cutting depth was found to be low. It was found that while the feed rate increased, the dependent variable increased and the tool nose radius decreased.

We propose an on-the-fly statistical learning method to make a qualitative reduced-order model of the dynamics of a premixed flame quantitatively accurate. This physics- informed data-driven method is based on the statistically optimal combination of (i) a reduced-order model of the dynamics of a premixed flame with a level-set method, (ii) high-quality data, which can be provided by experiments and/or high-fidelity simulations, and (iii) assimilation of the data into the reduced-order model to improve the prediction of the dynamics of the premixed flame. The reduced-order model learns the state and the parameters of the premixed flame on the fly with the ensemble Kalman filter, which is a Bayesian filter used in the data assimilation of high-dimensional dynamical systems, e.g., in weather forecasting. The proposed method and algorithm are applied to two test cases with relevance to reacting flow and instability. First, the capabilities of the framework are demonstrated in a twin experiment, where the assimilated data are produced from the same model as that used in prediction. Second, the assimilated data are extracted from a high-fidelity reacting-flow direct numerical simulation (DNS). The results are analyzed by using Bayesian statistics, which provide the uncertainties of the calculations. This method opens up new possibilities for on-the-fly optimal calibration of computationally cheap reduced-order models when experimental data become available, for example, from sensors.

The Danish energy system is undergoing a transition from a system based on storable fossil fuels to a system based on fluctuating renewable energy sources. At the same time, more of and more of the energy system is becoming electrified; transportation, heating and fuel usage in industry and elsewhere. This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model. The results show that even with a limited short-term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrated wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long-term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps and electric vehicles in the long-term future overshadows any effects of changes in hourly demand curve profiles. International Journal of Sustainable Energy Planning and Management, Vol 7 (2015)

ON 16 NOVEMBER 2000, the final report of the World Commission on Dams (WCD) was launched in London, in the presence of South Africa’s former president Nelson Mandela. This represented a remarkable milestone in the history of dam policy and politics. During its two-year existence, WCD had conducted the most extensive review of research and evidence regarding the planning, impacts, and management of large dams. It had engaged with numerous stakeholders around the globe. It also made comprehensive recommendations about how to improve dam planning and management.

Hoang Lien National Park has a total area of 68569ha, located at an altitude of above sea 1000-3000m in the territory of the two provinces of Lai Chau and Lao Cai in Vietnam. It has a diversity of flora with 3252 species (including 775 endemic species and 236 endangered species), belonging to 1126 genera, 230 families and 6 different divisions. Due to the mountainous terrain, division diversity of Hoang Lien National Park’s vegetation is thus clearly characterized by high elevations. We have studied the distribution characteristics of the vegetation by high elevations in Hoang Lien National Park of Vietnam by the general survey methodology, fieldwork, remote sensing digital image processing and analysis and inheriting the preceding research results. The study results indicated the divisions in quantity, vegetation composition, especially differentiation of endemic and rare species in accordance with high elevations. Study results were preliminary used to suggest some orientations for preserving plant diversity in high elevations of the terrain. Vườn quốc gia Hoàng Liên có tổng diện tích 68569ha, nằm ở độ cao từ 1000-3000m so với mặt biển thuộc lãnh thổ hai tỉnh Lai Châu và Lào Cai của Việt Nam. Hệ thực vật của Vườn quốc gia Hoàng Liên rất phong phú với 3252 loài (trong đó có 775 loài đặc hữu và 236 loài quý hiếm), thuộc 1126 chi, 230 họ và 6 ngành khác nhau. Do địa hình núi cao, phân hóa đa dạng nên thảm thực vật của Vườn quốc gia Hoàng Liên có đặc trưng phân hóa theo đai cao rất rõ nét. Bằng các phương pháp điều tra tổng hợp, khảo sát thực địa, xử lí phân tích ảnh viễn thám và kế thừa các kết quả nghiên cứu đi trước nhóm tác giả đã tiến hành nghiên cứu đặc điểm phân bố thảm thực vật theo đai cao tại Vườn quốc gia Hoàng Liên của Việt Nam. Kết quả nghiên cứu chỉ rõ sự phân hoá về số lượng, thành phần hệ thực vật theo đai cao và phân hóa thành phần loài đặc hữu và quý hiếm theo đai cao. Bước đầu nghiên cứu đề xuất một vài định hướng bảo tồn đa dạng thực vật theo đai cao của địa hình. Journal of Vietnamese Environment, Vol 6 No 2 (2014)

As grid price rises and the feed-in tariff declines, the economics of local storage become increasingly lucrative to the system owner. The attractiveness of a local storage investment is compounded in the presence of a PV grid injection cap. The larger the PV system size is relative to this cap level, the greater the opportunity exists to charge the local storage with PV production that would otherwise be dissipated without credit. This study utilizes two household demand profiles that represent the extremes of the potential for local PV self-consumption and, consequently, the range of economic potential that exists for local storage to be coupled with residential PV systems. A series of algorithms were subsequently developed to analyze the related benefit potential of delayed storage charging to target instances of excess PV production in relation to the grid injection cap. 28th European Photovoltaic Solar Energy Conference and Exhibition; 3751-3756

Recently, development projects have provided support to governments to facilitate technology transfer for climate change adaptation and mitigation. These include the Technology Needs Assessment (TNA) funded by the Global Environmental Facility (GEF). In the TNA project, which was implemented in ten African countries from 2010 to 2013, dedicated government committees have prioritized climate change mitigation technologies and developed action plans for the diffusion of the selected technologies. The project results show that solar PV is high on the agenda in Africa. Six out of ten countries in the region prioritized solar PV, and action plans for the diffusion of solar home systems were put forward in Cote d’Ivoire, Kenya, Mali and Senegal, while the implementation of grid-connected systems was proposed in Rwanda, Mali and Senegal. The project reports and technology action plans prepared in these six countries are used as the basis for comparing how solar PV is perceived in these countries and how policy measures enabling environmental adjustments and investment programmes are being planned to promote diffusion of the technology in these different contexts. 1st Africa Photovoltaic Solar Energy Conference and Exhibition Proceedings, AfricaPVSEC 2014

Seasonal variation coupled with heavy axle loading is the key factor in rapid road deterioration in Pakistan. The serviceability loss is further accelerated by the fact that truck drivers and owners consider overloading as a profitable practice unaware of the adverse effects of this practice. Weigh-in-motion data from two stations located between two major cities of Pakistan (Peshawar and Rawalpindi) on Grand Trunk Road (N-5) were collected and analyzed. Analysis of variance and comparison of actual and designed truck factor were performed to identify the most damaging axle truck type. It was found that axle truck type 3 (single/tandem axle) is most damaging among all truck types. The actual truck factor for axle truck type 3 is 6.4 times greater than design truck factor. Regression expressions of different forms were also investigated to determine the relationship between truck factor and gross vehicular weight for the specified truck types. An optimum generalization strategy was used to prevent over-generalization and ensure accuracy. For data analysis, 75% of data was used to develop regression models and remaining 25% was to validate those models. The results show that the polynomial expressions performed best and provide a robust relationship that can be employed by the highway authorities to estimate truck factor from gross vehicular weight with a high degree of confidence. It was also observed that damaging effect of various types of trucks was very severe and quite high.