MODEL predictive CONTROLler is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive SIMPLIFIED MODEL Predictive CONTROL (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the CONTROLler is designed and the CONTROLler coefficients are directly calculated. The proposed method is validated via simulations for both slow and fast time varying systems. Simulation results indicate the CONTROLler ability for tracking references in the presence of plant’s time varying parameters. In addition, an analytical tuning method for adjusting prediction horizon is proposed based on optimization of the objective function. It leads to a simple formula including the MODEL parameters, and an indirect adaptive CONTROLler can be designed based on the analytical formula. Simulation results indicate a better performance for the tuned CONTROLler. Finally, experimental tests are performed to show the effectiveness of the proposed methodologies.

Background & Aims: Different scoring systems are used in order to assess the functional quality of intensive care units (ICU) and to predict the required costs and facilities of intensive cares. Variety of scoring systems has been explained that each has advantages and disadvantages. In this study SIMPLIFIED Acute Physiology Score-III (SAPS-III) and Mortality Probability MODEL-III (MPM-III) were compared. Materials & Methods: The current cross-sectional study was conducted on 240 non-traumatic patients admitted at ICU of Al-Zahra Hospital in 2016-17. Patients' information including demographics, mean of systolic, diastolic and arterial pressure, pulse rate, respiratory rate, temperature, Glasgow Coma Scale(GCS), WBC, hematocrit, bilirubin, creatinine, arterial blood gas, and the presence of underlying diseases was gathered from the records for measurement of MPM-III and SAPS-III scores and then they were compared. Results: This study was conducted on 240 non-traumatic patients. Discrimination of MPM-III in cutoff point of 0. 17 was 0. 83(P<0. 001; 95%CI: 0. 765-0. 898), sensitivity and specificity of this test in prediction of non-traumatic mortality was 82% and 73%, respectively. Discrimination of SAPS-III in cut-off of 48. 5 was 0. 78(P<0. 001; 95%CI: 0. 72-0. 84), while its sensitivity and specificity was 83% and 70%, respectively. Duration of ICU hospitalization (P=0. 028 and 0. 002) and duration of intubation (P=0. 001 and <0. 001) had direct association with mortality based on both scoring systems while total duration of hospitalization was only significant in SAPSIII (P=0. 002). Conclusion: Comparison of SAPS-III and MPM-III in non-traumatic patients presented a higher discrimination ability for MPM-III. In addition, findings showed that mortality in MPM-III was in association with duration of ICU admission and intubation while for SAPS-III, in addition to previous factors, total duration of hospitalization was associated as well.

Background: Intensive care unit (ICU) is among the most important hospital wards. Variety of scoring systems for evaluation of patients' status and prediction of hospitalization outcomes in ICU has been raised that each has strong and weak points; assessment of these characteristics tends to promote new scoring systems. The current study compared scoring systems of Mortality Probability MODEL-III (MPM-III) and SIMPLIFIED Acute Physiology Score-III (SAPS-III) in trauma patients in ICU. Methods: This randomized cross-sectional study was conducted on 200 patients admitted in ICU because of trauma in years 2016-17. Patients' information including demographics, mean of systolic, diastolic, and arterial blood pressure, pulse, respiratory rate, temperature, Glasgow coma scale (GCS), arterial gas analysis, white blood cell (WBC) counts, hematocrit, bilirubin, creatinine, type of admission, and presence of underlying diseases were extracted from records; MPM-III and SAPS-III were measured for these patients and compared. Findings: MPM-III scoring system had discrimination of 0. 935 [95% confidence interval (95%CI): 0. 89-0. 97; P < 0. 001) in cut-off point of 0. 13, and its sensitivity and specificity was 87% and 84%, respectively. For SAPS-III system, in cut-off point of 0. 13, the discrimination was 0. 77 (95%CI: 0. 69-0. 85; P < 0. 001), with the sensitivity of 80% and specificity of 68%. Based on both MPM-III and SAPS-III systems, mortality was in correlation with duration of ICU admission (P = 0. 001 for both systems) and duration of intubation (P < 0. 001 for both systems), while only for SAPS-III, total duration of hospitalization was in correlation with mortality (P < 0. 001). Conclusion: MPM-III scoring system was superior to SAPS-III regarding discrimination power in trauma patients. In addition, based on both systems, mortality rate was in direct association with days of ICU admission and intubation duration.

The purpose of this paper is to develop a comprehensive maturity MODEL for command and CONTROL. For this purpose, the inductive research method has been used to design the maturity MODEL. Thus, firstly, the most prominent maturity MODELs in command and CONTROL, including the conceptual maturity MODEL, the headquarters maturity MODEL, the NATO MODEL, and the maturity MODEL of integrated command and CONTROL centers (ICCCs) were analyzed. Among the studied MODELs, the NATO MODEL is more comprehencive, so we chose it as a basis for developing our MODEL. Then, the stages and variables of maturity were analyzed using the focus group method. The findings of the research show that some important characteristics of the command and CONTROL maturity  have been neglected in the basic MODEL. Therefore, the innovation of this research is to add new features to achieve a more comprehensive MODEL. The result is a MODEL containing 5 levels and 20 variables. Validation of the MODEL has been done through comparative study and focus group method, which should be further strengthened by case studies and survey researches.

The aim of this work is to CONTROL the flow around ground vehicles by active or/and passive strategies. The active CONTROL is achieved by steady, pulsed or closed-loop jets located at the back of the SIMPLIFIED car MODEL. The passive CONTROL is performed using porous layers between the solid body and the fluid in order to modify the shear forces. The two previous CONTROL methods can be coupled to improve the drag reduction.

Enhancement in the aerodynamic performance of wings and airfoils is very notable when Active Flow CONTROL (AFC) is applied to Short Take-off and Landing aircraft (STOL). The present numerical study shows the application of steady, pulsed and synthetic tangential jets applied to the plain flap shoulder of a modified NASA Trapezoidal Wing. Pulsed jets are MODELed by sinusoidal and square waveforms while synthetic jets are MODELed only by pure sine waveform. The freestream airflow conditions are Mach number equal to 0. 2 and Reynolds number equal to 4. 3 million based on the mean aerodynamic chord. The presented simulations are two-dimensional and based on RANS for steady jet cases and URANS for pulsed and synthetic cases, compiled with the open-source suite SU2 and adapted for time varying boundary conditions. Numerical results for modified configurations based on the same baseline wing profile considering different leading edges, jet slot height, flap position, blowing mass flow, type and frequency of the jets are presented. Curves of pressure coefficient distribution revealed a substantial influence upstream of the AFC, around the slat and main element. The jet slot height analysis showed that the lift gain is also influenced by the slot size due to the change of the local flow velocity considering the same blowing momentum coefficient. Regarding the jet frequency, no significant differences on the lift coefficients were found between the reduced frequencies F+ equal to 1 and 2. Results of aerodynamic loads showed an improved lift coefficient in relation to the baseline airfoil when pulsed and steady jets are employed. Pulsed jets under square waveform were effective even at high deflected flap condition at 50°, with a significant gain in the lift coefficient of 36%, in relation to the unCONTROLled case, combined with a drag reduction of 20%, and a decrease in mass flow up to 49% in relation to the steady jet for the same lift gain. Although sine and square waveform results presented similar improvements for lift, the drag is around 15% higher for the former. When compared with the steady jet case, the mass flow reduction is 36% for the sinewave. Synthetic jets with zero-net-mass-flux proved superior to the baseline conventional multi-element airfoil only with deployed flap at 50°, where a modest lift improvement of 5% was observed.

Mass dynamic analysis of structures requires high computational cost which leads to time consuming process. Therefore, it is necessary to use SIMPLIFIED MODELs that significantly reduce the time of the analysis with appro-priate and acceptable accuracy compared to the detailed MODEL. In this research, a SIMPLIFIED MODEL of multi degrees of freedom for the dual system of moment resisting frame and shear wall with regular plan is proposed. MVLEM MODEL is used for shear wall and Substitute Frame is used for RC moment resisting frame. The MVLEM MODEL consists of axial elements that simulate the flexural behavior of the shear wall and the substi-tute frame uses one bay frame instead of multi-bay moment resisting frames. In the end, the accuracy and speed of MODELing and analysis of the SIMPLIFIED MODEL compared to the original MODEL as a detailed frame. The results show that the SIMPLIFIED MODEL provides seismic responses with less than 10% error and analysis time less than 30 times compared to the detailed MODEL.

This work introduces a structural integrity assessment strategy for Jacket structures based on the finite element MODEL updating and a novel SIMPLIFIED method. Hereof, MODEL reducing and MODEL updating procedure is established based on a optimization technique. Since the number of measured degrees of freedom is most of the time restricted in practice, this paper represents a methodology using the cross MODEL cross mode method (CMCM) in combination with an iterative procedure which uses limited, spatially incomplete modal information. This research is an empirical study on a laboratory MODEL of a jacket structure with the aim of establishing Refined SIMPLIFIED FE MODEL (RSM) to conduct damage detection. In addition to elimination of uncertainty effects in the damage detection results, RSM technique is employed because of practical considerations and also this technique provides a fast damage zone diagnosis procedure. Also, improved reduction scheme is utilized based on static reduction scheme to carry out damage detection in jacket structure.

In this paper, a SIMPLIFIED CONTROL algorithm based on unit vector template generation (UVTG) is proposed for a stardelta supported three-phase four-wire (3P-4W) unified power quality conditioner (UPQC) topology for the improvement of different power quality problems. Different topologies reported in literature for 3P-4W UPQC use active compensation for the mitigation of source neutral current along with other power quality (PQ) problems, while the uses of passive elements for the mitigation of source neutral current are advantageous over the active compensation due to ruggedness and less complexity of CONTROL. Hence, in this paper a star-delta transformer is connected in shunt near the load for mitigation of source neutral current, while three-leg voltage source inverters (VSIs) based shunt and series active power filters (APFs) of 3P-4W UPQC mitigate the current and voltage based distortions, respectively. A simple CONTROL algorithm based on Unit Vector Template Generation (UVTG) is used as a CONTROL strategy of UPQC for mitigation of different PQ problems. In this CONTROL scheme, the current/voltage CONTROL is applied over the fundamental supply currents/load voltages instead of fast changing APFs currents/voltages, thereby reducing the effects of computational delay and the required sensors. The performance of the proposed topology of UPQC is analyzed through simulations results using MATLAB software with its Simulink and Power System Block set toolboxes.