فهرست مطالب محمد ریاحی

It is of special importance to distinguish legal matters from factual ones in the interpretation of contracts in order to clarify the scope of the (first instance) judge's authority and the jurisdiction of the Supreme Court. The court judge enjoys absolute authority in the process of interpretation to ascertain the intention of the parties, and the Supreme Court cannot restrict such authority. However, there are exceptions where the Supreme Court can intervene and overturn a judgment. For example, when a judge distorts a contract under the pretext of interpretation, the Supreme Court may overturn the judgment. It merits mention that the Supreme Court is responsible for supervising the proper enforcement of rules in courts; in other words, it controls the legal issues of interpretation. To put it simply, when a judge makes a mistake in aligning a judgment with the facts, the Supreme Court will overturn the judgment. Comparing Iran’s legal system with that of France, this descriptive-analytical study aims to distinguish the legal aspects/matters of contracts from their factual aspects/matters. This will clarify the scope of the Supreme Court's intervention and the authority of the court of first instance in interpreting contracts, considering that the Iranian legislature expresses no opinion in this regard. Typically, in both Iranian and French legal systems, the Supreme Court can only exercise jurisdiction over legal matters.

Additive manufacturing (AM) is based on the deposition of materials with high precision to make a final part or component using different methods. This process is considered one of the main developments in the fourth industrial revolution and is still growing. There are many different types of additive manufacturing methods, and today, the use of efficient inspection methods is required to ensure a certain level of quality and detect defects and discontinuities in the industry. Today, in industry, non-destructive testing (NDT) is widely used, especially in additive manufacturing, to ensure efficient quality control and predictive maintenance without changing the properties and initial state of materials. Each non-destructive testing method is based on different physical principles and the correct selection and use of each test depends on the application, manufacturing process, type of material and possible discontinuities and many other things. The most common defects created in AM parts in terms of appearance include porosity, entrapped impurity, cracks, and material defects, which are mainly caused by changes in manufacturing parameters, injection parameters, and initial material properties. In this article, the performance of non-destructive tests was investigated to inspect the parts produced by the additive manufacturing method. These tests include visual inspection, liquid penetrant testing, magnetic particle testing, eddy current testing, ultrasonic testing, XCT, acoustic emission testing and thermography test. The application of each of the mentioned NDT methods in additive manufacturing and their suitability for detecting the defects of parts manufactured by AM method were investigated. Also, the sensitivity, advantages and disadvantages of each method were evaluated and the types of defects and the ability to detect these defects by NDT methods were mentioned. Considering that there are 7 categories of production methods in additive manufacturing, in this research, the application of each NDT test for different categories of AM process was discussed and the challenges in each were mentioned.

Misunderstanding of reality and belief that something is right, wrong or vice versa is called mistake. Understanding the concept of wrong is not possible simply, because the meaning of right and wrong is relative and temporary. However, what as a mistake requires the performance guarantee, is the event that the belief of the contracting party is not in accordance with the reality. As a result, the mistake in the legal system of Iran and France distorts the will, not the subject of the contract. In Iranian Law, a mistake is sometimes a flaw in the intention and sometimes a flaw in the intention. Based on this, the performance guarantee considered by the legislator is null and void, respectively and in other cases, according to the principle of firmness of contracts, no executive guarantee has been considered for it. In French Law, it sometimes invalidates the will and sometimes impairs it, and in other cases it does not affect the validity of the contract; Based on this, mistakes are divided into obstacles, effective and ineffective, and the guarantee of its implementation is absolute, relative, and in some cases, creating the right of cancellation; An ineffective mistake does not disrupt the contract. The purpose of this article is to explain the nature and position of the mistake by applying the descriptive-analytical method and with a comparative look at the French legal system, and to study its effects in order to provide a suitable solution to solve complex problems that usually occupy the courts of law.

Nowadays, traffic has become a challenge for everyone. One of the ways to overcome this problem is to make cars more intelligent. In this research, perception enhancement of the environment has been considered by using the data fusion of ultrasonic data and stereo vision. In this research, the researchers have suggested the cut stereo vision method by ultrasonic data in such a way that the accuracy and speed of obstacle detection will increase simultaneously in smart cars. Therefore, in addition to the similarity of the light intensity in the matching window, the neighboring pixels' depth has been used in a way to achieve the goals mentioned above without exponentially increasing the computational load. So, two types of compliance windows have been defined. One window is similar to the cut stereo method, and the other is called the inference window. By using the proposed inference window based on cut stereo vision, it is possible to apply the influence of the depth of neighboring pixels at a sufficient and effective level, which is reduced 61.57% error compared to the previous study. Furthermore, according to the suggested way of implementation on the graphic card, the obstacle detection speed has improved by 43.93% compared to the previous parallel implementation. The mentioned improvements make it possible to detect the environment in each meter of a car's movement if its speed is 178.1 km/h rather than 100.8km/h in the previous study. So current study produces smart cars more reliable.

The anticipatory ownership was treated as juridical institution and was treated as alternative of ownership. Despite the disagreement that was seen on its nature, it’s possible to know the institution as appropriate cause. Sometimes the appropriation cause is a right like pre-emption and sometimes is a contract that creates the cause of ownership and gain of ownership suspend after conclusion of contract. There is any doubt for the possibility of legal conveyance. But, for voluntary transfer it is necessary to study each applicability in its special terms. Also, it is possible to  imagine usurpation and destruction of anticipatory ownerships object in terms of non-contractual obligations. This study draws on analytical – descriptive methods.

In French law, ownership is the legal relation between a person and an object. Accordingly, a lease contract is not deemed a possessory contract proper. Because the property interests are actually nonexistent (i.e. imaginary) and intangible. In this light, Article 1709 of French Civil code provides that a party binds himself to have the other enjoy a thing during a certain time. That is, the contract is of a liability nature. However, in Article 466 of Iran’s Civil Code, itself based on Emamieh Jurisprudence, a tenancy contract accords ownership of interests to the tenant. The reason is that ownership in Emamieh Jurisprudence and Iran’s law is more extensive than that in French law. In the former, ownership is arbitrary and the object of the contract can be as much arbitrary. To affect ownership, there is no need for tangible or concrete thing, because ownership is essential and does not require a substance. This theory can help shed light on contract consequences such as destruction of hired object or leasehold and the contradiction between Repudiation of Contract and a Void Contract in Article 483 and 489 of Iran’s Civil Code, respectively. This study draws on analytical – descriptive methods.

The sale of a future property is a transaction in which the property does not yet exist at the time of the contract’s conclusion but will exist in the future. The property may be passing of ownership or an ascertained (i.e. definite and specific) object. This study investigated the latter type, that is, the sale of a future ascertained object. There are two obstacles to the validity of this contract. The first obstacle is the impossibility of ownership of nonexistent. The second obstacle is that this type of sale is uncertain (Bai' al-Gharar). However, from an analytical point of view, neither of the said obstacles can impair the validity of this type of contract because both obstacles can be overcome. In French Civil Code, making commitments concerning a future property is explicitly authorized. In English law, the sale of future property, which is a type of unascertained property, is not known as a transfer, but as an agreement to transfer. In the Iranian legal system, the legislator has not addressed this subject through a general rule. However, belief in the accuracy can be improved through foundations governing the legal system and some sporadic legal texts including Article 842 of the Civil Code. This study is conducted by means of a descriptive-analytical method.

To achieve competitive advantage, organizations need to build the infrastructure that can be achieved through the implementation of investment projects in the organization. On the other hand, limited resources prevent the implementation of all potential projects, and prioritizing and selecting among them would be necessary. When evaluating investment projects, it is important to consider a variety of criteria and organization's mission and strategy along with well-known economic indicators in a decision-making model to make it closer to the real-world situations. In many organizations, unclear viewpoints, and sometimes personal tastes, instead of having an integrated system according to specific and measured criteria for decision making, influences the choice of the projects. This paper presents a multi-criteria prioritization model of integrative AHP and SAW, for evaluating investment projects in Mobarakeh Steel Company, which describes the appropriate criteria and how to measure them along with the priority determination method. Applying of the proposed model in practice to systematically select the projects reduces the chance of project elimination after approval, while decreases the personal manner. The application of the proposed model on the set of investment projects of the company in 1997 shows the compliance of more than 85% of the obtained prioritization with what has happened in practice. T

Maintenance is one of the most important elements in any industry. Next to manufacturing, it probably has utmost importance in the production of industrialgoods.It has even higher priority when rotary machines are used. Having an appropriate algorithm for maintenance can prevent human and financial problems in such industries. In recent times, various methods of remaining useful life (RUL) prognosis have been proposed for rotary machines, but there is not a comprehensive review article that can well differentiate different methods. Herein, after describing the meaning of remaining useful life, the three most commonly used prognosis methods, including data-driven approach, model-based approach and hybrid prognostics approach, are elaborated upon. Subsequent to that, concept and mathematics of RUL in rotary machines for each method, have been discussed. Toward the end, there are constructive suggestions for researchers in this field in terms of dealing with RUL and PHM.

Metal additive manufacturing is an innovative technology that opens up new visions in any industrial field these days. This technology is growing rapidly, entering various industries every day. After over 30 years from the introduction of metal additive manufacturing into the industrial world, today’s demand is to make mechanical parts with high precision by metal additive manufacturing. Until now, methods like high precision grinding or micro-machining processes are used to make more precise dimensions in parts. Those methods have their own limits that could be eliminated with additive manufacturing. In this paper, attempts are made to compare conventional precise processes with metal additive manufacturing from different aspects. Surface finish in these two categories is discussed and some advice for improving the surface quality of metal additive manufacturing parts is proposed. Applicability and utilization of metal additive manufacturing as a precise metal fabrication method in various industries are also discussed.

During the operation of rotating machines in large industries such as power plants, the journal bearing failures are numerous. In order to avoid catastrophic damages in bearings and reducing the causes, evaluation of the root causes of bearing failures is important. In this paper, we investigate the root causes of failure in journal bearings, using one of the powerful methods of maintenance fields, which has been named failure mode and effect analysis. In order to collect bearing failures data, have been referred to the six power plants and failures information is obtained. Using this data and charts related to the occurrence probability, detection probability and severity rates which are the main parameters of this method for determining the risk priority number, the failure mode and effect analysis method has been implemented. According to this method, the main failure has been identified as wear. Then, using the well-known model of bearing wear geometries and computational fluid dynamics analysis for solving Navier-Stocks equations, effects of wear on the bearing load capacity, maximum lubrication pressure, in the different locations of wear, in the lower half of the bearing, has been investigated. Finally, the results of the finite element analysis have been compared to the results of the theory and solving the Sommerfeld-Harrison equation for bearing without wear. Also, to reduce the effects of this failure, another bearing geometry has been proposed in a similar situation with a load capacity greater than the custom one.

Nature of additive manufacturing processes dictate direction-related properties to the final parts and this degree of anisotropy is highly dependenton the process parameters and machine setup, Consequently, the formed properties in such materials should be known in any direction and in any aspect related to the origins assumed initially. There are several methods including destructive and non-destructive techniques for specifying mechanical properties in parts. Using ultrasonic testing, as a nondestructive method, in order to determine elastic constants for rocks, woods, composite and wrought materials, represent its reliability and validity, as well as its repeatability and non-destructivity through years. In this paper, 9 independent elastic constant for orthotropic additively manufactured direct metal laser sintering (DMLS) parts are determined from longitudinal and transverse ultrasound velocities via contact ultrasonic testing for different manufacturing process parameters. This work also carried out comparisons between mechanical properties of as-built parts in three principle directions, as well as ultrasound wave velocities.

The design of this study was done to investigate the effects of inhibiting the activity of beta-adrenergic receptors by supplementation of different concentrations of propranolol (as a none-selective inhibitor of beta- adrenergic receptors) on some of the performance characteristics in laying hens at the end of the economic production period and the qualitative traits of eggs. The experiment was performed in a complete randomized design, over a 26-day period, using 64 laying hens (90 weeks’ age) included 4 treatments (including control treatment and propranolol treatment with concentrations of 1, 2, and 3 mg Per kilogram of live body weight) with 4 repetitions and each repetition consisted of 4 birds, and some of the performance characteristics, follicular size (F1-F5) and egg quality were measured and calculated. The data obtained from the performance characteristics show that the usage of all concentrations of this inhibitor causes the significant increase in the laying percentage, improvement of feed conversion ratio. Propranolol also significantly increased feed intake and F1 follicle size at a concentration of 3 mg. Regarding the qualitative parameters of eggs, the usage of this inhibitor causes the significant increase in the thickness of the egg shell, the significant increase in the shell weight and ratio of the shell to the total weight of the eggs and the improvement of the Hue index in concentrations of 2 and 3 mg propranolol in treated birds. Therefore, it can be concluded that supplementation of different concentrations of propranolol in this study has been capable of improving some of the performance and qualitative characteristics of eggs in laying hens at the end of the production period.

In this study, by using signal processing methods, the propagation behavior of the waves in a GF/EP composite plate is practically investigated, and the propagated wave signals variations is analyzed as well. First, multiple paths of signal propagation was designed, based on a network of piezoelectric transducers, which have a dual role of excitor and sensor, which demarcates the plate into four areas, comprsing healthy, with delamination, hole and notch areas. Then by defining two types of damage indexes, under the concept of wavelet transform, the extraction features of the signals associated with each of the four areas in 40 directions and 9 conditions are compared. In the final step, the effect of each damage on the signal waves, by applying the numerical values of the damage indexes, at the joint time and frequency domain, was studied. The results show that by the proposed method, it is possible to detect and distinguish the wave behavior analysis affected by different damages in the structure; furthermore, it is a reasonable and convenient alternative technique for the conventional nondestructive testing.

Prognostic Health Management (PHM) is a new philosophy in maintenance that deals with the diagnosis and prognosis of failures and defects in devices PHM in rotary machines is usually utilizing the analysis of vibration signals, acoustic emission, temperature or oil analysis. By having a proper health index obtained from signal analysis, it is possible to detect system defects and prepare the device for maintenance operation. In this paper, the acoustic emission signals of a milling machine are used to detect tool wear or breakage. First, with wavelet analysis, the signal noise was reduced in order to achieve a suitable analysis to select the health index. Here, three mother wavelet functions db4, sym5 and haar and three thresholding methods are used. Research has shown that the parent functions sym5 and haar with low penalize threshold method, with 3 levels of analysis, have the lowest MSE of 0.0018 and 0.0019, respectively. In the next step, fourteen signal feature functions were extracted and compared with each other. Among the functions studied for the health index, the result showed that from healthy to unhealthy instrument in addition to the root mean square (RMS) function with 10% change, signal root square with 10%, entropy 15%, energy 28%, impact factor 33%, the maximum signal index of 48% can also be suitable criteria for the health index.

During the recent decades, a considerable increase in milk production has occurred in dairy cows. But it has been accompanied by an unwanted increase in different diseases and disorders such as metabolic disturbances. Negative energy balance can cause ketosis and fatty liver. Disturbances in macro-minerals such as calcium, phosphorus and magnesium, microminerals, proteins and enzymes often occur days to weeks after parturition. One or the most challenging post-parturient problem, is ruminal acidosis, that it mainly occurs due to changes in ration by using high fermentable carbohydrates to support milk production. All of mentioned disturbances can affect the hoof health and causing lameness in dairy cows. Laminitis is an important sequel of metabolic disturbances and ruminal acidosis in combination with inappropriate housing and management. Lameness can affect cow health and comfort, causing considerable economic losses in dairy industry.

Reduce the cost of unscheduled shutdown and enhance the reliability of systems, is one of the important goals for various industries that could be achieved by condition monitoring. Cavitation is a common phenomenon in centrifugal pumps which causes the damage and its true identification in early stage is too important and help to increase the life of pump. In this paper cavitation is identified by use of Artificial Immune Net (AIN) that is modeled on the function of the human immune system. For this purpose, first data collection were done by a laboratory setup and various features extracted form vibration and current signals, in next step, feature selection and dimensions reduction were done by artificial immune method, then with AIN method, the system condition was identified. Finally, for comparing the results of this study with other methods, first feature selection and dimensions reduction were down by the PCA method then fault detection were down by nonlinear supportive vector machine (SVM), multi-layer artificial neural network (MLP), K-means and FCM methods with features of PCA and AIN methods. The results shown that AIN methods have more precise than other methods.

ABSTRACT Condition Assessment is one of the most significant techniques of the equipment health management. PHM methodology cycle, is a developed form of Condition Based Maintenance (CBM). Condition Assessment is the most important step of this cycle. In this study, based on the model presented, using equipment Condition Assessment, the Remaining Useful Life (RUL) is estimated. Using the simulation and forecasting of a new feature for vibration of the equipment by Autoregressive Markov Regime Switching (ARMRS) method, equipment health condition is determined. Prior to forecasting the condition of the equipment, the equipment degradation state is determined by the fuzzy C-means clustering method. Based on the current state of equipment and pre-determined state of degradation, the Remaining Useful Life of the equipment is estimated. In order to evaluate the model, sensor data for PHM 2012 challenge have been used to forecast the bearing’s Remaining Useful Life And the results of the study have been compared with the winning results. One of the specifications of the proposed model is to determine the confidence intervals for Remaining Useful Life. Its innovations include the use of fuzzy clustering and evidence theory to integrate data and use Autoregressive Markov Regime Switching to prognosis.

Acoustic emission is one of the most important technique in None Distructive Test, that is able to evaluate crack growth in steel element of structure and is efficient in order to condition monitoring for deployment on in-service bridge component and these data can be used for schedule planning for maintanance of bridge structure. In line of experiments and empirical research, samples of structural steel (St52) were used as compact tension specimen in axial tensile fatigue test in order to study the crack growth. In this study, application of acoustic emission technique for health monitoring and determination of crack length in components of steel structure which are nuder axial fatigue load are investigated by using experimental test result, for this purpose correlation between acoustic emission parameters such a energy rate, count rate and etc and crack length and fatigue life has been studied. Finally by using the extrcted data from acoustic emission and fatigue test result, and least mean square regression analysis, the constants value for relation between crack length and acoustic emission parameters have been determined.

Pipelines are widely used in transporting large quantities of water and sewage over long distances. These valuable infrastructures attract public attention only when they fail. The quantitative and early detection of defects in sewer pipelines is very important in order to avoid severe consequences. In many countries, sewer pipeline inspection is usually carried out using CCTV (Closed-Circuit TV) cameras and off-line human surveys through raw image assessment for failure identification. CCTV-based techniques have some limitations that restrict their implementation. One of the disadvantages of CCTV-based techniques is the lack of visibility in the interior of the pipes. The other disadvantage of CCTV-based techniques is the poor quality of the obtained imagesbecause of difficult lighting conditions. In consequence, CCTV-based techniques can only detect gross defects reliably. In recent decades, thermography, microwave, laser, and sonar-based techniques have been proposed to complement the conventional CCTV-based technique and to improve inspection results. Also, new inspection devices employing multiple sensors and being capable of carrying out remote sewer inspection tasks have been proposed. This paper presents an overview of the conventional and novel inspection technologies for sewer pipelines. Furthermore, different types of robots for in pipe inspection tasks are discussed

Condition assessment is one of the most significant techniques of equipment health, repairs, maintenance, and management. Prognostics and Health Managemen (PHM) methodology cycle is a developed form of Condition Based Maintenance (CBM). Condition assessment is the most important step of this cycle. In this study, based on the presented model, the Remaining Useful Life (RUL) is estimated using equipment condition assessment. Using the simulation and forecasting of a new feature for the vibration of the equipment (Kurtosis-Entropy) by Autoregressive Markov Regime Switching (AMRS) method, equipment health condition is determined. Prior to forecasting the condition of the equipment, the equipment degradation state is determined by the fuzzy C-means clustering method. Based on the current state of equipment and pre-determined state of degradation, the remaining useful life of the equipment is estimated. In order to evaluate the model, the experimental data from the FEMTO-ST Institute, which is provided to estimate the remaining useful life of the bearing, was used and the results of the study are compared with the rival models. The innovation of this paper is the use of fuzzy C-means, a new approach to evidence theory for data fusion, and the use of the Markov switching model for prediction.

Journal bearings are vastly used in major industries such as power generation, oil and gas production, refineries, and the like. Thus, much investigation and study has taken place for more effective maintenance and fault detection of these bearings. An effective method in maintenance for these bearings is Root Cause Analysis (RCA) that tools like FMEA and FTA are used in it. In this paper, initially meanwhile investigation of journal bearing failures prioritizing of them have been down by using FMEA and FTA. For this purpose, expert opinion and field data collection were used in six gas power stations of country and by used them RPN are calculated for faults. Finally considering to RPN result and the importance of wear in journal bearing, this issue is simulated in COMSOL software and using Navier-Stokes equations and load capacity is investigated. At least some suggestions about geometry of journal bearing were presented to improve its performance

Using methods based on artificial intelligence to reduce the role of human interpretations in data analysis and obtaining the favorable results, in line with increasing the speed, reducing the errors and adjustment of the costs in the nondestructive evaluation and structural health monitoring is seriously concerned by researchers.
In this study, the design and implementation of a structural health monitoring system is performed by the intelligent signal processing of the ultrasonic waves in order to identify and classify the three common defects in the composite plate-like structures. By creating three types of damages including delamination, crack and hole in the multi-layer composite plate made of glass fiber reinforced polymer and dividing it into 4 different zones, 9 piezoelectric transducers with dual role of actuator and sensor are attached with their network arrangement and the propagated signals in the four mentioned zones on the 12 paths in three different directions including 240 signals were stored. In the next step, extraction of the features from the signals is conducted by the advanced signal processing techniques such as wavelet transform and the findings have been used to train a neural network of advanced multilayer perceptron by back-propagation error method.
The results show that the trained neural network algorithm is able to differentiate between the intact zone from the damaged ones. In addition, it has classified the types of current defects and damages in the structure with the acceptable efficiency (the average is about 80%), which can be generalized to the different conditions.

Performance of cutting fluids in machining of different materials is critical importance in order to improve the efficiency of any machining process. The objective of this research is investigation the effects of cryogenic cooling on tool wear and power consumption in the turning process of AISI 304 austenitic stainless steel. Cutting speed and cutting time each at three levels were selected as cutting variables. Response surface methodology (RSM), employing a face-centered central composite design scheme, has been used to plan and analyze the experiments. The relationships between machining parameters and output variables were modeled using RSM. Analysis of variance (ANOVA) was performed to check the adequacy of the mathematical model and its respective variables. The results showed a good agreement between the measured tool wear and power consumption and predicted values obtained by developed models. Suitable mathematical models for the response outputs were obtained using the ANOVA technique, in which significant terms were chosen according to their p values less than 0.05 (95% of confidence interval). When experiments and analysis of results were done, it is observed that tool wear was decreased till 67.5% and power consumption was decreased till 24% in cryogenic cooling method when compared with dry machining.

In this study, ultrasonic guided waves have been generated by means of a system developed for producing the desired signal needed for excitation of guided waves and a piezoelectric sensor. After propagating, waves are measured using an ultrasonic probe and recorded via a digital oscilloscope. Subsequently, the received signals have been processed and filtered for de-noising in order to be compared. As investigating the parameters influencing the inspection ability of these waves, the receiving probe has been moved along the pipe and by changing number of input signal pulses and sweeping the frequency; signals have been recorded at the frequency in which amplitude is maximum. By sweeping the frequency in the range of 30 to 40 kHz, it is possible to receive an appropriate signal in each point of the test piece.