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An indirect measurement method based on an analytical formula is presented to estimate the effective inductance which is associated with the winding resonances of an iron core transformer winding. It is applicable to any 1- $\Phi$ or 3- $\Phi$ (Y, $\Delta$ ) winding, with any condition of the neutral. A new analytical method is developed using authors’ recent work (which linked the harmonic sum of squares of natural frequencies of a winding to its inductances and capacitances). Data about the trough (SCNFs) or peak (OCNFs) frequencies corresponding to two FRAs is the only required input; one FRA corresponding to the nominal condition and another measured after connecting a known lumped capacitor across the winding. Details of derivations for each 1- $\Phi$ and 3- $\Phi$ configuration is initially presented. Thereafter, experimental results are discussed on 1- $\Phi$ and 3- $\Phi$ , 33 kV, 3.5 MVA winding setup, where any desired winding connection can be configured and examined. Then, results on two actual transformers are discussed to prove method's practical implementability. Finally, some preliminary thoughts on using this newly defined quantity for assessing mechanical integrity of winding is briefly examined.

Previous findings show that collaborative interviews with pairs of eyewitnesses can result in more accurate testimony than individual interviews, and that partners remember more together if they acknowledge, repeat, rephrase and elaborate upon each other's contributions. In the present study, we investigated whether these findings differ for pairs of acquainted and unacquainted partners, respectively. Participants viewed a violent movie in the cinema and took part in three eyewitness interviews approximately five days later. The first and the last interview were always individual. The second interview was individual in the nominal condition (N = 22 pairs), collaborative with a known partner in the acquainted condition (N = 21 pairs), and collaborative with a stranger in the unacquainted condition (N = 20 pairs). We replicated benefits of collaborative eyewitness interviews, in terms of error pruning as well as delayed cross-cuing. However, we found no significant differences between acquainted and unacquainted pairs, neither in recall performance nor in retrieval strategies during the collaborative interview. Regardless of acquaintance, pairs who elaborated upon each other's contributions during the collaborative interview, remembered more together. The findings are evaluated within the theoretical framework of transactive memory. Practical implications for investigative interviewers are discussed.

This paper investigates the offline neural network based-fault tolerant control for an aircraft that suffers vertical-tail damage. First, the damaged model of the aircraft is obtained, and the external disturbance is estimated by a disturbance observer then, an optimal control scheme is proposed to control the aircraft in nominal condition. This optimal control scheme is developed into faulty condition by the offline neural networks. The simulation results show the effectiveness of the proposed method in comparison to the existing methods in the literature.

The purpose of this research is to develop a compact humidifier with novel ceramic foam corrugated packing, which is conducive to the improvement of the flexibility of humid air turbine cycles, thus has a potential in commercial application. The packing size is calculated with an analytic model based on the Merkel theory and energy effectiveness-NTU function. The simplified structures of the air and water distributors are proposed according to the special characteristics of packing. The evaluation of this humidifier has been carried out by means of experimental data obtained from a mHAT system. Both the steady state performance at off-design conditions and dynamic behavior at start-up process are presented and analyzed. At nominal condition, the humidifier shows a pinch of 12 °C and a relatively pressure loss of 0.59% operating pressure. With the load decreasing from 100% to 50%, the inlet and outlet fluid temperature as well as the outlet air humid ratio will all decrease, but the maximum decrement is not more than 11%. Due to the great thermal capacitance, especially that of the water in its bottom section, a relative slow response of the humidifier has been observed.

As the technology node gets smaller and smaller, the benefit from Sub-Resolution Assist Features (SRAF) becomes significant in EUV lithography which makes SRAFs a must-have tool for next generation beyond 7nm technology. When considering EUV specific effects, the metrics that need to be accounted for include Image Log-Slope (ILS), Process Variability (PV Band), common Depth of Focus (cDOF), and Image Shift (ImS) through focus. When these critical factors are accounted for during the EUV mask generation the optimization become much more complicated and challenging and necessitates the need for SRAFs beyond 7nm. SRAF helps enhance not only the PV Band, but more importantly helps boost the ILS, which is one of the key factors for improving stochastic effect in EUV. However, ILS is just one of the important image quality metric that we should focus on. For metal layers, Image Shift is another key factor which can have a big impact on overlay. ImS at the nominal condition could be compensated by Optical Proximity Correction (OPC), but image shift through focus can hardly be tuned by the main feature correction. The image shift through focus can be mitigated by SRAF insertion. Strong 3D mask effects can cause best focuses of different patterns to be far apart in EUV, which can cause an unusable cDOF even when the individual depth of focus values of all the patterns are not bad. SRAFs can be inserted to improve the individual depth of focus and align the best focuses together to help enhance the common process window. When taking account of various different EUV specific metrics mentioned above, then the most critical question for the next generation beyond 7nm is “How to define the cost function for mask optimization with SRAFs?” (Figure 1, EUV mask optimization flow for next generation beyond 7nm). In this study the image quality metrics including ILS, PVBand, cDOF, and ImS are evaluated. For each optimization schema using different cost functions, we examine the cost function metric and its impact on the other image quality metrics. We also present the potential trade-offs together with the analysis. Furthermore, multiple cross cost functions are defined for SRAF optimization and the results are analyzed accordingly. Both contact and metal layer patterns representing next generation beyond 7nm design rules are investigated. In our testing, symmetric standard sources from ASML NXE3400 is examined and the results are compared and analyzed.

PurposeProton dose distribution is sensitive to uncertainties in range estimation and patient positioning. Currently, the proton robustness is managed by worst-case scenario optimization methods, which are computationally inefficient. To overcome these challenges, we develop a novel intensity-modulated proton therapy (IMPT) optimization method that integrates dose fidelity with a sensitivity term that describes dose perturbation as the result of range and positioning uncertainties.MethodsIn the integrated optimization framework, the optimization cost function is formulated to include two terms: a dose fidelity term and a robustness term penalizing the inner product of the scanning spot sensitivity and intensity. The sensitivity of an IMPT scanning spot to perturbations is defined as the dose distribution variation induced by range and positioning errors. To evaluate the sensitivity, the spatial gradient of the dose distribution of a specific spot is first calculated. The spot sensitivity is then determined by the total absolute value of the directional gradients of all affected voxels. The fast iterative shrinkage-thresholding algorithm is used to solve the optimization problem. This method was tested on three skull base tumor (SBT) patients and three bilateral head-and-neck (H&N) patients. The proposed sensitivity-regularized method (SenR) was implemented on both clinic target volume (CTV) and planning target volume (PTV). They were compared with conventional PTV-based optimization method (Conv) and CTV-based voxel-wise worst-case scenario optimization approach (WC).ResultsUnder the nominal condition without uncertainties, the three methods achieved similar CTV dose coverage, while the CTV-based SenR approach better spared organs at risks (OARs) compared with the WC approach, with an average reduction of [Dmean, Dmax] of [4.72, 3.38] GyRBE for the SBT cases and [2.54, 3.33]GyRBE for the H&N cases. The OAR sparing of the PTV-based SenR method was comparable with the WC method. The WC method, and SenR approaches all improved the plan robustness from the conventional PTV-based method. On average, under range uncertainties, the lowest [D95%, V95%, V100%] of CTV were increased from [93.75%, 88.47%, 47.37%] in the Conv method, to [99.28%, 99.51%, 86.64%] in the WC method, [97.71%, 97.85%, 81.65%] in the SenR-CTV method and [98.77%, 99.30%, 85.12%] in the SenR-PTV method, respectively. Under setup uncertainties, the average lowest [D95%, V95%, V100%] of CTV were increased from [95.35%, 94.92%, 65.12%] in the Conv method, to [99.43%, 99.63%, 87.12%] in the WC method, [96.97%, 97.13%, 77.86%] in the SenR-CTV method, and [98.21%, 98.34%, 83.88%] in the SenR-PTV method, respectively. The runtime of the SenR optimization is eight times shorter than that of the voxel-wise worst-case method.ConclusionWe developed a novel computationally efficient robust optimization method for IMPT. The robustness is calculated as the spot sensitivity to both range and shift perturbations. The dose fidelity term is then regularized by the sensitivity term for the flexibility and trade-off between the dosimetry and the robustness. In the stress test, SenR is more resilient to unexpected uncertainties. These advantages in combination with its fast computation time make it a viable candidate for clinical IMPT planning.

This study considers the orbit insertion targeting problem for guidance of a multi-stage space launch vehicle. To design guidance algorithm for a particular mission target, the orbit designation method should be determined first, as the target orbit of closed-loop guidance during the upper stage flight is usually specified at the end of the final stage. We investigate some advantages of this single target approach over the one with intermediate targets in addition to the final target by comparing them in various flight conditions using an explicit guidance algorithm. We notice that in some cases application of the single targeting can be rather tricky and thus propose here an extended version of the single targeting algorithm that can be applied to problems where the target orbit plane has to be changed during the upper stages flight. We also demonstrate that this pseudo-single target method can be applied to these kinds of problems smoothly in contrast to the conventional single target algorithms by conducting numerical simulations for disturbed off-nominal conditions as well as for the nominal condition.

This paper presents automatic generation control (AGC) of three unequal area thermal systems with single reheat turbine and appropriate generation rate constraints (GRC) in each area. A two degree of freedom (2DOF) controller called 2DOF-integral plus double derivative (2DOF-IDD) is proposed for the first time in AGC as secondary controller. Secondary controller gains and other parameters are optimized simultaneously using a more recent evolutionary computational technique called Cuckoo Search algorithm (CS). The system dynamic responses for various 2DOF controllers such as 2DOF-PI, 2DOF-PID, and 2DOF-DD are compared. Investigations reveal that responses with 2DOF-IDD are better than others. Performance of several FACTS devices such as Static synchronous series compensator (SSSC), Thyristor controlled series capacitor (TCSC), Thyristor controlled phase shifter (TCPS), and Interline power flow controller (IPFC) in presence of 2DOF-IDD controller are compared and found that the dynamic responses with IPFC are better than others. For the first time in AGC, a case study is performed with placement of IPFC and observed that IPFC present in all three areas of the system performs better. Sensitivity analysis reveals that the CS optimized 2DOF-IDD controller parameters obtained in presence of IPFC in all three areas at nominal condition of loading and size of step load perturbation (SLP) are robust and need not be reset with wide changes in system loading and SLP. Also, the comparison of convergence curve of various algorithms reveals that CS algorithm converges much faster than others.

The new Federal Aviation Administration (FAA) Small Unmanned Aircraft rule (Part 107) marks the first national regulations for commercial operation of small unmanned aircraft systems (sUAS) under 55 pounds within the National Airspace System (NAS). Although sUAS flights may not be performed beyond visual line-of-sight or over non- participant structures and people, safety of sUAS operations must still be maintained and tracked at all times. Moreover, future safety-critical operation of sUAS (e.g., for package delivery) are already being conceived and tested. NASA's Unmanned Aircraft System Trac Management (UTM) concept aims to facilitate the safe use of low-altitude airspace for sUAS operations. This paper introduces the UTM Risk Assessment Framework (URAF) which was developed to provide real-time safety evaluation and tracking capability within the UTM concept. The URAF uses Bayesian Belief Networks (BBNs) to propagate off -nominal condition probabilities based on real-time component failure indicators. This information is then used to assess the risk to people on the ground by calculating the potential impact area and the effects of the impact. The visual representation of the expected area of impact and the nominal risk level can assist operators and controllers with dynamic trajectory planning and execution. The URAF was applied to a case study to illustrate the concept.

This paper investigates controlling the blood glucose level and automatic insulin delivery rate in type I diabetic patients, based on the glucose-insulin regulatory system considering time delays. The respective nonlinear multiple time delay model is linearized around a nominal condition, and then the T-SMTD form is derived for PDC design. Throughout this goal, a novel LMI-based stabilization criterion for T-S Fuzzy systems with multiple time delays is proposed. The performance of the proposed controller and the effectiveness of considering time delay are verified in simulations by using the original glucose-insulin metabolism model presented by Li et al., 2006.

Basal insulin infusion rate which should be adjusted to increase or decrease insulin delivery with the varying blood sugar level plays a key role in type 1 diabetes mellitus (T1DM) patients for maintaining the blood glucose level approximately steady within reference range in order to avoid the complications developed from diabetes. This paper proposes an effective hybrid particle swarm optimization (HPSO) algorithm for solving the basal insulin infusion rate problem. In HPSO, bad experience lesson learning scheme and local search based on chaotic dynamics are proposed to make a good balance between global exploration and local exploitation. Simulation results based on a set of well-known optimization benchmark instances and the basal insulin infusion rate adjustment problem for T1DM demonstrate the effectiveness of the proposed HPSO. In silico tests on standard virtual subject via HPSO show that under nominal condition the blood glucose concentrations could be kept within a range of 80---150 mg/dL within less than 5 days; meanwhile, in case of random variations in meal timings within $$\pm $$±60 min or meal amounts within $$\pm $$±75 % deviation from the nominal values, the blood glucose concentrations could be kept within the safe regions.

This paper presents the automatic generation control (AGC) of an unequal three area thermal system with single reheat turbine and generation rate constraints of 3%/min in each area. A two degree of freedom (2DOF) controller called 2DOF – integral plus double derivative (2DOF – IDD) is proposed for the first time in AGC as secondary controller. Secondary controller gains and other parameters are simultaneously optimized using a more recent and powerful evolutionary computational technique called Cuckoo search algorithm (CS). The system dynamic responses obtained with 2DOF – IDD controller are compared with that obtained with other 2DOF controllers such as 2DOF – Proportional-Integral (2DOF – PI), 2DOF Proportional – Integral-Derivative (2DOF – PID). Investigations reveals that 2DOF – PI, and 2DOF – PID provide more or less same response where as 2DOF – IDD controller provides much better response than the others. Sensitivity analysis reveals that the CS optimized 2DOF – IDD controller parameters obtained at nominal condition of loading and nominal size of step load perturbation (SLP) are robust and need not be reset with wide changes in system loading and (SLP).

A mechanism known as Negative-bias Temperature Instability (NBTI) degrades a main electrical parameters of a circuit especially in terms of performance. So far, the circuit design available at present are only focussed on high performance circuit without considering the circuit reliability and robustness. In this paper, the main circuit performances of high performance FinFET flip-flop such as delay time, and power were studied with the presence of the NBTI degradation. The aging analysis was verified using a 16nm High Performance Predictive Technology Model (PTM) based on different commands available at Synopsys HSPICE. The results shown that the circuit under the longer dynamic NBTI simulation produces the highest impact in the increasing of gate delay and decrease in the average power reduction from a fresh simulation until the aged stress time under a nominal condition. In addition, the circuit performance under a varied stress condition such as temperature and negative stress gate bias were also studied.

This article presents a data-driven method of pattern identification for in-situ monitoring of fatigue damage in polycrystalline alloys that are commonly used in aerospace structures. The concept is built upon analytic signal space partitioning of ultrasonic data sequences for symbolic dynamic filtering of the underlying information. The statistical patterns of evolving damage are generated for real-time monitoring of the possible structural degradation under fatigue load. The proposed method is capable of detecting small anomalies (i.e. deviations from the nominal condition) in the material microstructure and thereby generating early warnings on damage initiation. The damage monitoring algorithm has been validated on time series data of ultrasonic sensors from a fatigue test apparatus, where the behavioural pattern changes accrue because of the evolving fatigue damage in polycrystalline alloys.

The main cause of performance degradation in entrained-bed slagging gasification systems is attributed to evolution of structural damage in the refractory walls. Early detection of such damage is necessary to avert unscheduled shutdown of a gasification plant. This paper develops an integrated computer simulation model of a generic entrained-bed slagging gasifier for formulation of a damage prediction algorithm with the objective of real-time degradation monitoring and condition-based maintenance of refractory walls. The integrated simulation model yields: (a) quasi-steady-state spatial temperature profiles at any cross-section of the gasification system, and (b) dynamic response of the refractory wall temperature that is measured by an array of sensors installed at specified locations on the external surface of the gasifier wall. The key idea for early detection of refractory-wall damage is built upon the fact that a local anomaly (i.e. deviation from the nominal condition) is likely to influence the temperature gradient in the refractory wall due to changes in the thermal impedance. The information from dynamic response of refractory temperature is extracted in a compressed form as statistical patterns of evolving anomaly through usage of a recently reported data-driven pattern identification tool called symbolic dynamic filtering (SDF). The results of this model-based investigation show that the proposed anomaly detection and damage prediction method is potentially capable of characterizing the health status of refractory walls in particular and the entire gasification system in general. The SDF algorithms in this paper are implemented on the MATLAB platform and are interfaced with the gasification plant simulation model for emulation of real-time degradation monitoring.

Several extended state observer (ESO) based controllers for flight vehicle are investigated and compared in nominal condition and uncertain condition, respectively. Firstly, the flight vehicle model with parameter uncertainties and external disturbances are presented. And then, the baseline controllers, such as input-output linearization control (IOL), sliding mode control (SMC), and model predictive control (MPC) are proposed. The uncertain parameters and external disturbances are integrated and regarded as the lumped disturbance, which is then estimated by the ESO. Consequently, several ESO-based controllers are investigated and compared with the baseline controllers. The comparison results have validated that the ESO-based controllers are of strong robustness and extraordinary efficiency.

Autonomous guided airdrop systems based on steerable, ram-air parafoils generally offer significant improvements in payload delivery accuracy compared to unguided airdrop. In the event of a malfunction or rigging error, the gliding and steering ability of the parafoil canopy can exhibit extremely large deviations from the nominal condition. Significant damage and deviations from the nominal flight characteristics can break the most advanced flight controllers, even ones employing adaptive elements to account for small variations in flight speed, atmospheric wind conditions, and small turning biases. This work details the theory and application of a hyperadaptive algorithm for the estimation and control of a parafoil and payload system through the implementation of a Hammerstein model. Integration of system identification methods into an advanced guidance algorithm allows for dynamic and steady state characterization for accurate landings at various levels of system damage.

A comprehensive parametric study for a Fischer-Tropsch (FT) synthesis process has been conducted to investigate the relation between process parameters and reactor characteristics such as conversion, selectivity, multiplicity, and stability. A flexible model was employed for this purpose, featuring the dependence of Anderson-Shultz-Flory (ASF) factor on composition and temperature. All variable process parameters in industrial FT reactors were subject to variation, including reaction temperature, reactor pressure, feed ratio, inlet mass flux, feed temperature, heat transfer coefficient, catalyst concentration, catalyst activity, etc. While typical trade-off was encountered in most cases, i.e., the change of a parameter in one direction enhances one aspect but deteriorating another, the change of feed conditions gave some promising results. It has been found that decreasing the feed rate (or increasing the residence time) and/or lowering the feed concentration can successfully enhance the conversion up to more than 90% for our specific case, without hurting the product selectivity as well as effectively condense the region of multiple steady states. The benefits and limitations accompanied with the variation of the parameters were discussed in detail and a rational start-up strategy was proposed based on the preceding results. It is shown that the decrease of inlet mass flux (say, 85% decrease of the feed rate or 60% decrease of the feed concentration from the nominal condition chosen here) or the decrease of H2/CO ratio (specifically, below about 0.25), or their combination can eliminate multiple steady states. The resulting unique relation between temperature and manipulated variable (i.e., coolant flow rate) appears to assure a safe arrival at the target condition at the start-up stage.

Background: There have been no large-scale analyses of resource utilization comparing the overall costs to treat pediatric patients vs adult patients. Likewise, there have been no studies evaluating the costs of the various components of hospitalization (e.g., accommodation, laboratory, radiology, and drugs) among adult and pediatric populations. Methods: To study the effect of age on the costs of treating patients, we have evaluated 43 conditions with matching diagnosis-related groups (DRGs) for children and adults. Using a database developed by the University HealthSystems Consortium, we examined the major non-physician components of hospital costs, including accommodation, surgery, pharmacy, radiology, and laboratory for 1 346 028 patient admissions to 60 University hospitals. These costs were derived from the ratio of costs to charges based on the Centers for Medicare and Medicaid Services PPS UB-2 cost reports. Results: The total non-physician cost of treating adults was generally greater than that for children within paired DRGs. Some of this difference may be attributable to the overall longer stay of adults in hospital. For conditions that were nominally the same, radiology, laboratory, and drug costs, especially tended to be higher for adults than for children. This was most marked when the costs were evaluated on a per diem basis. There tended to be greater variability in the costs of treating children than adults within the paired DRGs, as evidenced by greater differences between the median and mean costs. Conclusions: Among University hospitals, the costs of managing children are typically less than for adults with the same nominal condition. In these hospitals, there tends to be less use of laboratory, radiology, and pharmacy services for children than for adults.

An investigation of magnetic core losses of an electrodeless fluorescent lamp is presented in this paper. These losses can be divided into two different kinds: static, which is related to hysteresis effects, and dynamical, associated to parasitic effects. Experimental results (at 25° C) demonstrate that the total losses, in nominal condition point, are approximately 3.18 W, what represent 3.18% of the power supplied to the lamp. In this same point, the static losses are approximately 1.31 W and the dynamic losses about 1.87 W. Based on this, the static losses represent about 41% of total loss related to the magnetic core while dynamical losses represents 59% of total loss.

In this paper a maiden attempt has been made to examine and investigates the effect of bacterial foraging (BF) optimized fractional order integral and derivative (FOID or IλDμ) controller in automatic generation control (AGC) of a multi-area thermal system considering single stage of reheat turbine and appropriate generation rate constraint (GRC). The performances of several classical integer-order (IO) controllers such as I, PI and PID controllers is evaluated and compared with IλDμ controller to assess the best controller. Investigation reveals that IλDμ controller provides better performance than the IO controllers in terms of settling time, reduced oscillations and peak overshoots. This paper employs bacterial foraging algorithm for optimization of gains and other parameters such as order of integrator (λ) and differentiator (μ) in case of IλDμ controller. Further, sensitivity analysis is carried out for the first time in the system considered to investigate the robustness of the optimum gains, λ and μ of IλDμ controllers obtained at nominal condition.

In order to attain an optimal operation, this paper proposes the minimization of the reactive power losses and a voltage stability index, taking into account the line drop compensation in the step-up transformers. The application is carried out in an equivalent of the Mexican power system, solved by genetic algorithms. Results are presented showing the advantages of the optimal operation with respect to a non-optimized nominal condition.

This work describes a re-configurable 0.5 V to 1.2 V, 10 MS/s to 100 MS/s, 10 b two-step pipeline ADC. The prototype ADC in a 0.13 um CMOS process demonstrates the measured DNL and INL within 0.35 LSB and 0.49 LSB, respectively. The ADC with an active die area of 0.98 mm2 shows the maximum SNDR and SFDR of 56.0 dB and 69.6 dB, respectively, and a power consumption of 19.2 mW at a nominal condition of 0.8 V and 60 MS/s.

As the preceding chapters in this volume have amply demonstrated, much useful knowledge concerning ecosystem structure and function can be obtained by subjecting estimated networks of material and energy flows in marine systems to the analytical techniques described in Kay et al. (1989, this volume). Usually, the data required for the network analysis techniques are identical to those necessary to begin the simulation modelling of these same systems-namely, the magnitudes of the stocks and flows. (Ducklow et al. 1989, this volume)

In this chapter the design of two different I.F. amplifiers intended for the vision channel of a television receiver according to the C.C.I.R. standards will be described. The difference between the two amplifiers lies in the methods by which automatic gain control is achieved. In one amplifier the system of reverse gain control is used, whereas in the other, forward gain control is applied.

A pseudo-LVDS driver has been designed in a 180 nm technology for operation up to 5 Gb/s. It contains parallel main driver units based on an H-bridge circuit steering a current on an external load. The number of active units is adjustable, to reduce switching capacitance and static current, and hence power consumption, if a smaller current swing can be tolerated. Pre-emphasis is applied with a capacitively coupled charge-injection circuit. In the nominal condition with a steering current of 4 mA over a 100 $\Omega$ termination resistor, it consumes 30 mW from a 1.8 V supply.

This paper deals with application of automatic generation control (AGC) to deregulated power system and makes a maiden attempt to provide a new practical AGC model to cater to the needs of a modern restructured hydro-thermal power system. Several DISCO Participation Matrix (DPM) and Area Participation Factor (APF) have been tried out and dynamic responses for frequency, tie flow and generations are obtained to examine the performance of the system in deregulated environment considering integral controllers. Investigation has been carried out to study the effect of generation rate constraint and the importance of APF in deregulated environment. Studies also reveal that the conventional integral controllers are quite robust and the optimum integral gains once set for nominal condition need not be changed for plusmn25% variations in system parameters and plusmn20% variations in operating load condition from their nominal values. The sensitivity of the optimal controller gains to DPM and APF has also been brought out. For the first time, studies have been carried out for the selection of suitable values for governor speed regulation parameter R for the hydro and thermal plants in the deregulated mode. System studies reveal the satisfactory operation of the hydro-thermal system conforming to the requirements in the deregulated environment