Rapidly predicting Kohn–Sham total energy using data-centric AI

Predicting material properties by solving the Kohn-Sham (KS) equation, which is the basis of modern computational approaches to electronic structures, has provided significant improvements in materials sciences. Despite its contributions, both DFT and DFTB calculations are limited by the number of electrons and atoms that translate into increasingly longer run-times. In this work we introduce a novel, data-centric machine learning framework that is used to rapidly and accurately predicate the KS total energy of anatase TiO 2 nanoparticles (NPs) at different temperatures using only a small amount of theoretical data. The proposed framework that we call co-modeling eliminates the need for experimental data and is general enough to be used over any NPs to determine electronic structure and, consequently, more efficiently study physical and chemical properties. We include a web service to demonstrate the effectiveness of our approach. © 2022, The Author(s)

Tailoring the structural properties and electronic structure of anatase, brookite and rutile phase TiO2 nanoparticles: DFTB calculations

In this study, we perform a theoretical investigation using the density functional tight-binding (DFTB) approach for the structural analysis and electronic structure of anatase, brookite and rutile phase TiO2 nanoparticles (NPs). Our results show that the number of Ti-O bonds is greater than that of O-O, while the number of Ti-Ti bonds is fewer. Thus, large amounts of O atoms prefer to connect to Ti atoms. The increase in the temperature of the NPs contributes to an increase in the interaction of Ti–O bonding, but a decrease in the O-O bonding. The segregation of Ti and O atoms shows that Ti atoms tend to co-locate at the center, while O atoms tend to reside on the surface. Increasing temperature causes a decrease of the bandgap from 3.59 to 2.62 eV for the brookite phase, which is much more energetically favorable compared to the bulk, while it could increase the bandgap from 3.15 to 3.61 eV for anatase phase. For three-phase TiO2 NPs, LUMO and Fermi levels decrease. The HOMO level of anatase phase NP decreases, but it increases for brookite and rutile phase TiO2 nanoparticles. An increase in the temperature contributes to the stabilization of anatase phase TiO2 NP due to a decrease in the HOMO energies. © 2020 Elsevier B.V

Büyükanne ve büyükbabalarda torun bakmanın depresyon ve yaşam kalitesine etkisi

Başlangıç seviyesi projesiAmaç: Bu araştırma “Büyükanne ve büyükbabalarda torun bakmanın depresyon ve yasam kalitesine etkisini incelemek amacıyla planlanmış ve uygulanmıştır. Materiyal ve Metod: Araştırma tanımlayıcı ve kesitsel niteliktedir. Denizli il merkezinde 60 yas üzeri torun bakan ve bakmayan büyükanne ve büyük babalar araştırmanın evrenini oluşturmuştur. Toplum sağlığı merkezlerinden rastlantısal olarak birer aile sağlığı merkezi seçilmiş ve her birinden ikişer aile hekimliği bölgesi randomizasyon örnekleme yöntemi ile belirlenmiştir. Örnekleme çıkan her bir aile hekimliği bölgesinde kayıtlı olan 60 yas üzeri yaslı nüfus, toplam nüfusa orantılanmış ve bölgelerden kaçar yaslının örnekleme alınacağı belirlenmiştir. Evreni bilinen örneklem formülüne göre araştırmaya alınacak örneklem sayısı 920 olarak bulunmuştur. Veri toplama araçları olarak; Birinci bölümde “Büyükanne, büyükbaba ve toruna yönelik tanıtıcı bilgi formu” “, İkinci bölümde Büyükanne ve babaların depresyon düzeylerini ölçebilmek için “Geriatrik Depresyon Ölçeği, Üçüncü bölümde ise, Büyük anne ve babaların yasam kalitesini belirlemek amacıyla Dünya Sağlık Örgütü Yasam kalitesi Ölçeği (WHOQOL –OLD ) kullanılmıştır. Araştırmaya başlamadan önce benzer örneklemde ön uygulama yapılmıştır. Verilerin değerlendirilmesinde, SPSS 11.0 programı kullanılmış ve veriler sayı yüzde dağılımları, Independent t testi, varyans analizi, ki kare ve korelasyon analizi ile değerlendirilmiştir. Bulgular: Arastırmaya katılan büyük anne ve büyükbabaların yas ortalaması 62.20±7.71dir. Büyükanne ve büyükbabaların %59.6’sını bayanlar, %42.2’si ilkokul mezunu, %91.9’u gelir getiren herhangi bir iste çalısmıyor, %46.2’sinin aylık geliri 500-999TL arasındadır. Büyükanne ve büyükbabaların %49.6’sı torun baktığını, %50.4’ü torun bakmadığını belirtmiştir. %40.3’ü torun bakmanın ekonomik yük getirmediğini, %47.4’ü bundan kazanç elde etmediğini, %17.5’i torun bakmanın kendisini daha mutlu hissettirdiğini, %11.0’ı ise torun bakmanın aşırı yorgunluğa neden olduğunu belirtmiştir. Büyükanne ve büyükbabaların yasam kalitesi değerlendirildiğinde, yasam kalitesi ölçeğinin duygusal işlevler ile ölüm ve ölmek alt boyutlarında torun bakan ve bakmayanlar arasında istatistiksel olarak anlamlı bir fark olduğu saptanmıştır ( p<0.05). Torun bakanların %23.6’sında depresyon riski görülürken, %76.4’ünde depresyon riski yoktur. Torun bakmayanların %33.4’ünde depresyon riski görülürken, %66.6’sında depresyon riski yoktur. Algılanan sağlık durumu ile depresyon görülme riski ve yasam kalitesi arasında istatistiksel olarak anlamlı bir ilişki olduğu belirlenmiştir. Sonuç ve Öneriler: Sonuç olarak, torun bakan büyükanne ve babalarda bakmayanlara göre depresyon görülme riskinin daha az olduğu, yine torun bakmanın yasam kalitesi ölçeğinin duygusal işlevler ile ölüm ve ölmek alt boyutlarında etkili olduğu belirlenmiştir. Subjektif sağlık algısı hem depresyon görülme riskinde hem de yaşam kalitesinde etkili bulunmuştur. Projenin bulguları ülkemizde bir ilki oluşturmuştur. Bu yüzden bu arastırmanın farklı örneklemlerde yapılması önerilmektedir.Purpose: This study was planned and carried out in order to observe the effect of grandmother and grandfather’s looking after grandchildren on depression and life quality. Material and Method: The study is descriptive and cross-sectional. The universe of the study was composed of grandmothers and grandfather over the age of 60 years and who look and do not look after grandchildren in Denizli. One family health center was chosen randomly from public health centers and two family practice areas per each center were detected with randomization sampling method. Population over the age of 60 years registered in each family practice area for sampling was proportioned to total population and how many elder people was to be taken for sampling was determined. Sampling to be included in the study according sampling formula was determined to be 920. As data collection tool; In the first section “Identifying Information Form for the grandmothers, grandfathers and grandchild; in the second section “Geriatric Depression Scale” in order to measure grandmothers and grandfathers’ depression level, in the third section World Health Organization Quality of Life Scale (WHOQOL – OLD) in order to determine life quality of grandmothers and grandfathers were used. For the evaluation of data; SPSS 11.0 program was used and data were evaluated with percentage distribution, Independent t test, variance analysis, chi square and correlation analysis. Findings: Average of age of grandmothers and grandfathers who are involved in the study is 62.20±7.71. 59.6% of the grandparents are female, 42.2% of them are graduate of primary education, 91.9% of them do not work in a job that brings an income, monthly income of 46.2% of them is between 500-900 TL. It was detected that 49.6% of the grandparents look after grandchildren and 50.4% do not. 40.3% of grandparents expressed that looking after grandchildren do not bring any economic burden to them, 47.4% expressed that they do not gain profit from it, 17.5% expressed that they feel themselves happy for looking after their grandchildren, 11.0% expressed that looking after children brought overfatigue. When life quality of grandparents were considered, it was detected that there was a statistically meaningful difference in the lower dimensions of emotional functions and death and dying of life quality scale between grandparents who look and do not after grandchildren ( p<0.05). There is a risk of depression in 23.6% of grandparents who do not look after grandchildren while there was no risk of depression in 66.6% of them. It was detected that there was a statistically meaningful relation between health condition and risk of depression and life quality. Results and Suggestions: As a result, it was detected that the risk of depression is lower in grandparents who look after grandchildren compared with those who do not look after grandchildren and that looking after grandchildren is effective in the lower dimensions of emotional functions and death and dying of life quality scale. Subjective health perception was found to be effective in both the risk of depression and life quality. Findings of the project were a first in our country. Therefore the study was suggested to be carried out in different samplings as well

Finsler Geometry for Two-Parameter Weibull Distribution Function

To construct the geometry in nonflat spaces in order to understand nature has great importance in terms of applied science. Finsler geometry allows accurate modeling and describing ability for asymmetric structures in this application area. In this paper, two-dimensional Finsler space metric function is obtained for Weibull distribution which is used in many applications in this area such as wind speed modeling. The metric definition for two-parameter Weibull probability density function which has shape (k) and scale (c) parameters in two-dimensional Finsler space is realized using a different approach by Finsler geometry. In addition, new probability and cumulative probability density functions based on Finsler geometry are proposed which can be used in many real world applications. For future studies, it is aimed at proposing more accurate models by using this novel approach than the models which have two-parameter Weibull probability density function, especially used for determination of wind energy potential of a region

Short-Term Solar Power Forecasting Based on CEEMDAN and Kernel Extreme Learning Machine

The use of renewable energy sources contributes to environmental awareness and sustainable development policy. The inexhaustible and nonpolluting nature of solar energy has attracted worldwide attention. Accurate forecasting of solar power is vital for the reliability and stability of power systems. However, the effect of the intermittency nature of solar radiation makes the development of accurate prediction models challenging. This paper presents a hybrid model based on Kernel Extreme Learning Machine (Kernel-ELM) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for short-term solar power forecasting. The decomposition technique increases the number of stable, stationary, and regular patterns of the original signals. Each decomposed signal is fed into Kernel-ELM. To validate the performance of the hybrid model, solar power data from the BSEU Renewable Energy Laboratory, measured at 5-minute intervals, are used. To validate the proposed model, its performance is compared to some state-of-the-art forecasting models with seasonal data. The results highlight the good performance of the proposed hybrid model compared to other classical algorithms according to the metrics

A New Approach Dependent On Risk To The Cost For The Expansion Of Electric Power Generation Systems

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2001Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2001Bu çalışmada, elektrik enerjisi üretim sistemlerinin genişletilmesine ilişkin maliyet hesabına, bilinen bir çok faktörün yanında şimdiye kadar açıkça ele alınmayan, bir risk faktörü katılmış ve üretim kapasitesinin planlanması çalışmalarında kullanılmıştır. Planlama probleminin çözümü için yalnızca maliyet minimizasyonu değil bunun yanında pek çok kritere dayanan karma tamsayılı programlama modeli kullanılmıştır. Buna ait amaç fonksiyonu oluşturulmuş ve bu amaç fonksiyonunun katsayıları olan birim yatırım ve birim işletme maliyetleri, önce risk dikkate alınmadan, daha sonra alınarak hesaplanmıştır. Bununla beraber, modele ait amaç fonksiyonunun diğer katsayıları ve karar değişkenleri de hesaplanarak problem genel bir karma tamsayılı programlama uygulaması olarak çözülmüştür. Modelin uygulaması, Türkiye’de 1999 – 2023 yılları arasındaki 24 yıllık bir planlama dönemi için gerçekleştirilmiştir. Bu planlama dönemi boyunca gereken sistem yükü, regresyon analizi yapılarak elde edilmiştir. Sonuçlar, tablolar halinde verilmiş ve çizilen grafikler yardımıyla karşılaştırılmıştır. Sonuç olarak, elektrik enerjisi üretim sistemlerinin genişletilmesi çalışmalarında yapılan üretim maliyeti hesaplarına risk oranının katılmasının, çok büyük bir maliyet artışı getirmediği ve bu şekilde elde edilecek ek gelirlerle tesislere çeşitli kazançlar sağlandığı görülmüştür.In this study, a risk factor in addition to other known ones is added to the cost for the expansion of electrical power generation systems and is used for the study of generation capacity planning. Due to the reasons like flexibility in modeling and providing highly accurate results, Mixed Integer Programming (MIP) model is chosen as a base for this study. This model, developed for generation expansion planning, which contains an objective function that minimizes the unit capital and operational costs consist of some inequality constraints. These costs of four different types of plants are calculated adding a risk factor and not. The application of the model is realized for 24 years of planning time between 1999 and 2023. Using regression analysis, the regression equation is determined. By referring to this equation, load forecasting for the planning period in Turkey is made. The results of the calculation are given as in both tables and figures, and the comparison of them are presented. As a result, it is concluded that joining a risk factor to the calculations of the generation cost in the study of power generation expansion planning doesn’t cause a high increase on the cost. Income provided in this way is used in many cases in power systems.DoktoraPh

EFFICIENCY ESTIMATION OF INDUCTION MOTORS AT DIFFERENT SIZES WITH ARTIFICIAL NEURAL NETWORKS AND LINEAR ESTIMATION USING CATALOG VALUES

Induction motors are the most preferable motors for the locomotives because of their simple but robust structure. The efficiency of the preferred motor is crucial for the limitation of the load pulled by the locomotive and suitability for the geographic conditions. For this reason, determining energy efficiency and operating conditions in induction motors is a very important issue. It is often not possible to experimentally realize the efficiency of induction motors, because this means that the motor is stopped during that time. This is an obstacle to the efficiency of the operator while trying to contribute to energy efficiency in the enterprise.   Therefore, estimation the efficiency of the motor provides a significant contribution to the operation and energy efficiency. Many studies have been made in the literature, which related to this issue. The difference of this study is that efficency estimations of induction motors at 17 different power are realized with artificial neural networks and linear prediction by looking at the values of speed, current and moment in the catalog. And also before the estimation is applied, the statistical relations between efficiency and moment, efficiency and speed, efficiency and current of the motor are also analyzed and presented

TÜRKİYE'DEKİ 22 BARALI 380 kV'LUK GÜÇ SİSTEMİ İÇİN EKONOMİK DAĞITIM VE OPTİMAL GÜÇ AKIŞI YÖNTEMLERİNİN KARŞILAŞTIRMALI ANALİZİ

Bu çalışmada, Türkiye'deki 380 kV'luk enerji iletim hatlarıyla birbirine bağlı EÜAŞ (Elektrik Üretim Anonim Şirketi) tarafından işletilen 8 tane termik santral bulunan 22 baralı 380 kV'luk güç sistemi için santrallerin en düşük maliyetle yük talebini karşılaması amacıyla ekonomik dağıtım ve optimal güç akışı yöntemleri kullanılmış ve bulunan sonuçlar karşılaştırmalı olarak analiz edilmiştir. Analiz sonuçları tablo ve şekillerle verilmiştir. Yapılan ekonomik dağıtım ve optimal güç akışı (OGA) analizleri, MATLAB®'de geliştirilen yazılımlarla gerçekleştirilmiştir. Aynı zamanda bu yazılımlar, grafiksel kullanıcı ara yüzü (GUI) oluşturularak farklı güç sistemleri için güç akışı, optimal güç akışı ve ekonomik dağıtım analizleri yapabilmektedir. Bu çalışmada kullanılan tüm veriler, TEİAŞ (Türkiye Elektrik İletim Anonim Şirketi) ve EÜAŞ 'tan alınmıştır

A Comparative Study of Three Different Mathematical Methods for Solving the Unit Commitment Problem

The unit commitment (UC) problem which is an important subject in power system engineering is solved by using Lagragian relaxation (LR), penalty function (PF), and augmented Lagrangian penalty function (ALPF) methods due to their higher solution quality and faster computational time than metaheuristic approaches. This problem is considered to be a nonlinear programming-(NP-) hard problem because it is nonlinear, mixed-integer, and nonconvex. These three methods used for solving the problem are based on dual optimization techniques. ALPF method which combines the algorithmic aspects of both LR and PF methods is firstly used for solving the UC problem. These methods are compared to each other based on feasible schedule for each stage, feasible cost, dual cost, duality gap, duration time, and number of iterations. The numerical results show that the ALPF method gives the best duality gap, feasible and dual cost instead of worse duration time and the number of iterations. The four-unit Tuncbilek thermal plant which is located in Kutahya region in Turkey is chosen as a test system in this study. The programs used for all the analyses are coded and implemented using general algebraic modeling system (GAMS)