Thermophysical Properties of 1,1,1,3,3-Pentafluorobutane (R365mfc)

This paper presents an experimental study on various thermophysical properties of a new fluoroalkane, 1,1,1,3,3-pentafluorobutane (R365mfc). The thermal conductivity of R365mfc was measured in the liquid phase near saturation conditions at temperatures between 263 and 333 K using a parallel plate instrument with an uncertainty of less than ±5%. For the measurement of the saturated liquid density between 273 and 353 K, a vibrating tube instrument was used. The uncertainty of the density measurements is less than ±0.1%. In addition, experimental data have been obtained for R365mfc under saturation conditions over a wide temperature range from about 253 to 460 K using light scattering techniques. Light scattering from the bulk fluid has been applied for measuring both the thermal diffusivity and the sound speed in the liquid and vapor phases. Light scattering by surface waves on a horizontal liquid–vapor interface has been used for the simultaneous determination of the surface tension and kinematic viscosity of the liquid phase. With the light scattering techniques, uncertainties of less than ±1.0, ±0.5, ±1.0, and ±1.2% have been achieved for the thermal diffusivity, the sound speed, the kinematic viscosity, and the surface tension, respectively.     

Mixed interval–fuzzy two-stage integer programming and its application to flood-diversion planning

Innovative prevention, adaptation, and mitigation approaches as well as policies for sustainable flood management continue to be challenges faced by decision-makers. In this study, a mixed interval–fuzzy two-stage integer programming (IFTIP) method is developed for flood-diversion planning under uncertainty. This method improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within the optimization framework. In its modelling formulation, economic penalties as corrective measures against any infeasibilities arising because of a particular realization of the uncertainties are taken into account. The method can also be used for analysing a variety of policy scenarios that are associated with different levels of economic penalties. A management problem in terms of flood control is studied to illustrate the applicability of the proposed approach. The results indicate that reasonable solutions have been generated. They can provide desired flood-diversion alternatives and capacity-expansion schemes with a minimized system cost and a maximized safety level. The developed IFTIP is also applicable to other management problems that involve uncertainties presented in multiple formats as well as complexities in policy dynamics.     

An Absolute Viscometer-Densimeter and Measurements of the Viscosity of Nitrogen, Methane, Helium, Neon, Argon, and Krypton over a Wide Range of Density and Temperature

An apparatus for the simultaneous measurement of viscosity and density of fluids is presented. The viscometer-densimeter covers a viscosity range up to 150 µPas and a density range up to 2000 kgm^–3 at temperatures from 233 to 523 K and pressures up to 30 MPa. Very accurate density measurements with uncertainties of ±0.02 to ±0.05% have always been carried out with this apparatus, although in its first version it was necessary to calibrate the viscosity measuring system on a reference fluid in order to achieve uncertainties of ±0.6 to ±1.0% in viscosity. After significant improvements, the apparatus now achieves uncertainties in viscosity of less than ±0.15% in the dilute gas region and less than ±0.4% for higher densities. Moreover, the viscosity measuring system can be described in an absolute way; calibration is no longer necessary. In order to test the advanced apparatus and to determine viscosity-density values of very high quality, comprehensive measurements on nitrogen, argon, and methane were carried out in the entire working range of the viscometer-densimeter. In addition, viscosity-density measurements on helium, neon, and krypton were made on two selected isotherms each. All measurements show that the estimated total uncertainty of ±0.15 to ±0.4% in viscosity and of ±0.02 to ±0.05% in density is clearly met. In order to verify the results of the combined viscometer-densimeter, a new apparatus for very accurate viscosity measurements was designed. While the working range of this apparatus is restricted to the dilute gas region, it yields uncertainties of less than ±0.07% in viscosity. Measurements carried out with this apparatus confirmed the previously measured values of the combined viscometer-densimeter within ±0.03%.     

On the use of the hybrid causal logic method in offshore risk analysis

In the Norwegian offshore oil and gas industry risk analyses have been used to provide decision support for more than 20 years. The focus has traditionally been on the planning phase, but during the last years a need for better risk analysis methods for the operational phase has been identified. Such methods should take human and organizational factors into consideration in a more explicit way than the traditional risk analysis methods do. Recently, a framework, called hybrid causal logic (HCL), has been developed based on traditional risk analysis tools combined with Bayesian belief networks (BBNs), using the aviation industry as a case. This paper reviews this framework and discusses its applicability for the offshore industry, and the relationship to existing research projects, such as the barrier and operational risk analysis project (BORA). The paper also addresses specific features of the framework and suggests a new approach for the probability assignment process. This approach simplifies the assignment process considerably without loosing the flexibility that is needed to properly reflect the phenomena being studied.     

Handling Uncertainties in Fault Tree Analysis by a Hybrid Probabilistic–Possibilistic Framework

Fault tree analysis is a method largely used in probabilistic risk assessment. Uncertainties should be properly handled in fault tree analyses to support a robust decision making. While many sources of uncertainties are considered, dependence uncertainties are not much explored. Such uncertainties can be labeled as ‘epistemic’ because of the way dependence is modeled. In practice, despite probability theory, alternative mathematical structures, including possibility theory and fuzzy set theory, for the representation of epistemic uncertainty can be used. In this article, a fuzzy β factor is considered to represent the failure dependence uncertainties among basic events. The relationship between β factor and system failure probability is analyzed to support the use of a hybrid probabilistic–possibilistic approach. As a result, a complete hybrid probabilistic–possibilistic framework is constructed. A case study of a high integrity pressure protection system is discussed. The results show that the proposed method provides decision makers a more accurate understanding of the system under analysis when failure dependencies are involved. Copyright © 2015 John Wiley & Sons, Ltd.     

A unified framework for risk and vulnerability analysis covering both safety and security

Recently, we have seen several attempts to establish adequate risk and vulnerability analyses tools and related management frameworks dealing not only with accidental events but also security problems. These attempts have been based on different analysis approaches and using alternative building blocks. In this paper, we discuss some of these and show how a unified framework for such analyses and management tasks can be developed. The framework is based on the use of probability as a measure of uncertainty, as seen through the eyes of the assessor, and define risk as the combination of possible consequences and related uncertainties. Risk and vulnerability characterizations are introduced incorporating ideas both from vulnerability analyses literature as well as from the risk classification scheme introduced by Renn and Klinke.     

Uncertainty quantification in dynamic system risk assessment: a new approach with randomness and fuzzy theory

Quantifying uncertainty during risk analysis has become an important part of effective decision-making and health risk assessment. However, most risk assessment studies struggle with uncertainty analysis and yet uncertainty with respect to model parameter values is of primary importance. Capturing uncertainty in risk assessment is vital in order to perform a sound risk analysis. In this paper, an approach to uncertainty analysis based on the fuzzy set theory and the Monte Carlo simulation is proposed. The question then arises as to how these two modes of representation of uncertainty can be combined for the purpose of estimating risk. The proposed method is applied to a propylene oxide polymerisation reactor. It takes into account both stochastic and epistemic uncertainties in the risk calculation. This study explores areas where random and fuzzy logic models may be applied to improve risk assessment in industrial plants with a dynamic system (change over time). It discusses the methodology and the process involved when using random and fuzzy logic systems for risk management.     

Quantification of epistemic and aleatory uncertainties in level-1 probabilistic safety assessment studies

There will be simplifying assumptions and idealizations in the availability models of complex processes and phenomena. These simplifications and idealizations generate uncertainties which can be classified as aleatory (arising due to randomness) and/or epistemic (due to lack of knowledge). The problem of acknowledging and treating uncertainty is vital for practical usability of reliability analysis results. The distinction of uncertainties is useful for taking the reliability/risk informed decisions with confidence and also for effective management of uncertainty. In level-1 probabilistic safety assessment (PSA) of nuclear power plants (NPP), the current practice is carrying out epistemic uncertainty analysis on the basis of a simple Monte-Carlo simulation by sampling the epistemic variables in the model. However, the aleatory uncertainty is neglected and point estimates of aleatory variables, viz., time to failure and time to repair are considered. Treatment of both types of uncertainties would require a two-phase Monte-Carlo simulation, outer loop samples epistemic variables and inner loop samples aleatory variables. A methodology based on two-phase Monte-Carlo simulation is presented for distinguishing both the kinds of uncertainty in the context of availability/reliability evaluation in level-1 PSA studies of NPP.     

Use of decision criteria based on expected values to support decision-making in a production assurance and safety setting

We consider decision problems related to production assurance and safety. The issue is to what extent we should use decision criteria based on expected values, such as the expected net present value (E[NPV]) and the expected cost per expected number of saved lives (ICAF), to guide the decision. Such criteria are recognised as practical tools for supporting decision-making under uncertainty, but is uncertainty adequately taken into account by these criteria? Based on the prevailing practice and the existing literature, we conclude that there is a need for a clarification of the rationale of these criteria. Adjustments of the standard approaches have been suggested to reflect risks and uncertainties, but can cautionary and precautionary concerns be replaced by formulae and mechanical procedures? These issues are discussed in the present paper, particularly addressing the company level. We argue that the search for such formulae and procedures should be replaced by a more balanced perspective acknowledging that there will always be a need for management review and judgment beyond the realm of the analyses. Most of the suggested adjustments of the E[NPV] and ICAF approaches should be avoided. They add more confusion than value.     

Quantification of margins and uncertainties of complex systems in the presence of aleatoric and epistemic uncertainty

Performance assessment of complex systems is ideally done through full system-level testing which is seldom available for high consequence systems. Further, a reality of engineering practice is that some features of system behavior are not known from experimental data, but from expert assessment, only. On the other hand, individual component data, which are part of the full system are more readily available. The lack of system level data and the complexity of the system lead to a need to build computational models of a system in a hierarchical or building block approach (from simple components to the full system). The models are then used for performance prediction in lieu of experiments, to estimate the confidence in the performance of these systems. Central to this are the need to quantify the uncertainties present in the system and to compare the system response to an expected performance measure. This is the basic idea behind Quantification of Margins and Uncertainties (QMU). QMU is applied in decision making—there are many uncertainties caused by inherent variability (aleatoric) in materials, configurations, environments, etc., and lack of information (epistemic) in models for deterministic and random variables that influence system behavior and performance. This paper proposes a methodology to quantify margins and uncertainty in the presence of both aleatoric and epistemic uncertainty. It presents a framework based on Bayes networks to use available data at multiple levels of complexity (i.e. components, subsystem, etc.) and demonstrates a method to incorporate epistemic uncertainty given in terms of intervals on a model parameter.     

Thermal conductivity andPVT measurements of pentafluoroethane (refrigerant HFC-125)

By means of the transient and steady-state coaxial cylinder methods, the thermal conductivity of pentafluoroethane was investigated at temperatures from 187 to 419 K and pressures from atmospheric to 6.0 MPa. The estimated uncertainty of the measured results is ±(2–3)%. The operation of the experimental apparatus was validated by measuring the thermal conductivity of R22 and R12. Determinations of the vapor pressure andPVT properties were carried out by a constant-volume apparatus for the temperature range 263 to 443 K, pressures up to 6 MPa, and densities from 36 to 516 kg m^–3. The uncertainties in temperature, pressure, and density are less than ±10 mK, ±0.08%, and ±0.1%, respectively.Paper presented at the Twelfth Symposium on Thermophysical Properties, June 19–24, 1994, Boulder, Colorado, U.S.A.     

Viscosity of Di-isodecylphthalate: A Potential Standard of Moderate Viscosity

The paper reports our first measurements of the viscosity of di-isodecylphthalate, which is a candidate for a reference material. At the same time it has a viscosity, which, at room temperature, is around 120 mPa · s, so that it can fulfill the need for a reference material more nearly matched to the needs of industry. The present measurements were carried out with a specially designed vibrating-wire viscometer over the temperature range 288–308 K and have an estimated uncertainty smaller than ±1.5%, following calibration against the viscosity of toluene. The instrument and results are presented here to encourage other measurements on the same material, by different techniques, which will lead eventually to the establishment of di-isodecylphthalate as a suitable reference material, as well as reference values for its viscosity.     

Understanding risk and uncertainty in supplier networks--a transaction cost approach

This study deals with managing risks in relationships between a larger final assembler and smaller suppliers. These relationships are often based on asymmetric cooperation where the smaller companies are highly dependent on the larger companies. This dependency can cause significant uncertainty for small and medium-sized enterprises that often operate with a narrow customer structure and minor negotiation power compared with their larger partners. The transaction cost approach (TCA) has been used as a framework for the analysis of uncertainties and risks related with these relationships. Despite the very comprehensive nature of empirical applications and theories of the transaction cost approach, these theories have not been very widely tested in the environment of small and medium-sized enterprises. Our study indicates that dependency and asymmetry are two major uncertainty and transaction cost causing drivers. Closer, long-term relationships are needed in order to minimize the transaction costs and risks. A smaller customer structure increases dependency and reduces partnership-specific transaction costs. The optimal strategy is to balance these opposite drivers. Options and linkages to the company's goals and strategies should therefore be the leading principles in balancing transaction cost uncertainty and risk. Empirical evidence from the electronics industry is presented. Alternative management approaches and further research areas are discussed.     

An Equation of State for 1,1,1-Trifluoroethane (R-143a)

A fundamental equation of state has been developed for 1,1,1-trifluoroethane (R-143a) using the dimensionless Helmholtz energy. The experimental thermodynamic property data, which cover temperatures from the triple point (161 K) to 433 K and pressures up to 35 MPa, are used to develop the present equation. These data are represented by the present equation within their reported experimental uncertainties: ±0.1% in density for both vapor and liquid phase P––T data, ±1% in isochoric specific heat capacities, and ±0.02% in the vapor phase speed-of-sound data. The extended range of validity of the present model covers temperatures from 160 to 650 K and pressures up to 50 MPa as verified by the thermodynamic behavior of the isobaric heat-capacity values over the entire fluid phase.     

Effects of densitometry,material mapping and load estimation uncertainties on the accuracy of patient-specific finite-element models of the scapula

Patient-specific biomechanical models including patient-specific finite-element (FE) models are considered potentially important tools for providing personalized healthcare to patients with musculoskeletal diseases. A multi-step procedure is often needed to generate a patient-specific FE model. As all involved steps are associated with certain levels of uncertainty, it is important to study how the uncertainties of individual components propagate to final simulation results. In this study, we considered a specific case of this problem where the uncertainties of the involved steps were known and the aim was to determine the uncertainty of the predicted strain distribution. The effects of uncertainties of three important components of patient-specific models, including bone density, musculoskeletal loads and the parameters of the material mapping relationship on the predicted strain distributions, were studied. It was found that the number of uncertain components and the level of their uncertainty determine the uncertainty of simulation results. The ‘average’ uncertainty values were found to be relatively small even for high levels of uncertainty in the components of the model. The ‘maximum’ uncertainty values were, however, quite high and occurred in the areas of the scapula that are of the greatest clinical relevance. In addition, the uncertainty of the simulation result was found to be dependent on the type of movement analysed, with abduction movements presenting consistently lower uncertainty values than flexion movements.     

Risk informed decision-making and its ethical basis

In decision-making under uncertainty there are two main questions that need to be evaluated: (i) What are the future consequences and associated uncertainties of an action, and (ii) what is a good (or right) decision or action. Philosophically these issues are categorized as epistemic questions (i.e. questions of knowledge) and ethical questions (i.e. questions of moral and norms). This paper discusses the second issue, and evaluates different risk management approaches for establishing good decisions, using different ethical theories as a basis. These theories include the utilitarian ethics of Bentley and Mills, and deontological ethics of Kant, Rawls and Habermas. The risk management approaches include cost–benefit analysis (CBA), minimum safety criterion, the ALARP principle and the precautionary principle.     

Radiation Thermometry Toward the Triple Point of Water?

The article describes and evaluates the possibility of using a high-temperature blackbody of accurately known thermodynamic temperature as a reference source for the determination of lower thermodynamic temperatures by spectral radiation thermometry. By applying various intermediate steps, this approach will allow spectral radiation thermometry to be used for the determination of the thermodynamic temperature of the triple point of water with a low uncertainty. The procedure for such an attempt is outlined, theoretical, and practical limits of the resulting uncertainty in thermodynamic temperature are given. The described experimental approach also provides a framework to calculate the uncertainties in determining the thermodynamic temperatures of the defining high-temperature fixed points of the International Temperature Scale of 1990 down to the triple point of water. The estimation of uncertainties is based on current and future values of the relevant contributing components. The uncertainty anticipated in determining the thermodynamic temperature of the triple point of water is 24 mK with current uncertainties and 1.9 mK in the future. Thus, the described approach yields uncertainties that are slightly higher, but comparable to, the tentative uncertainties of other methods—e.g., dielectric constant gas thermometry developed and applied within the framework of the new determination of the Boltzmann constant.     

Selective critique of risk assessments with recommendations for improving methodology and practise

Risk assessments are often criticised for defending activities that could harm the environment and human health. The risk assessments produce numbers which are used to prove that the risk associated with the activity is acceptable. In this way, risk assessments seem to be a tool generally serving business. Government agencies have based their regulations on the use of risk assessment and the prevailing practise is supported by the regulations. In this paper, we look more closely into this critique. Are risk assessments being misused or are risk assessments simply not a suitable tool for guiding decision-making in the face of risks and uncertainties? Is the use of risk assessments not servicing public interests? We argue that risk assessments may provide useful decision support but the quality of the risk assessments and the associated risk assessment processes need to be improved. In this paper, three main improvement areas (success factors) are identified and discussed: (1) the scientific basis of the risk assessments needs to be strengthened, (2) the risk assessments need to provide a much broader risk picture than what is typically the case today. Separate uncertainty analyses should be carried out, extending the traditional probabilistic-based analyses and (3) the cautionary and precautionary principles need to be seen as rational risk management approaches, and their application would, to a large extent, be based on risk and uncertainty assessments.     

PVTx and Isochoric Heat Capacity Measurements for Aqueous Methanol Solutions

Isochoric heat capacity and PVTx properties of an aqueous methanol solution (0.50 mass fraction or 0.36 mole fraction of methanol) were measured in the liquid phase with a twin-cell adiabatic calorimeter. Temperatures ranged from 333 to 422 K, and pressures ranged to 20 MPa. The calorimetric cell (70 cm³ capacity) was surrounded by adiabatic thermal shielding (high vacuum) and a steel-sheathed electric heater wound tightly on its surface. By combining the various sources of experimental uncertainty using a root-sum-of-squares formula, the relative uncertainty of C _V is estimated to be 2%. The uncertainties of the density, temperature (absolute), and pressure measurements are, respectively, about 0.1%, 40 mK, and ±7 kPa. The measured densities were used to calculate excess molar volumes that were compared with values calculated with a reliable model by Simonson et al. Good agreement within ±0.008 cm³mol^–1 (or ±0.03% of the density) was found between measured values of excess molar volume and those calculated from the model. Values of saturated liquid densities were determined by extrapolating experimental P-T data to the saturation curve.