High-pressure phase equilibrium in the {carbon dioxide (1) + 1-chloropropane (2)} binary system

Abstract The current study reports original vapour-liquid equilibrium (VLE) for the system {CO2 (1) + 1-chloropropane (2)}. The measurements have been performed over the entire pressure-composition range for the (303.15, 313.15 and 328.15) K isotherms. The values obtained have been used for comparison of four predictive approaches, namely the equation of state (EoS) of Peng and Robinson (PR), the Soave modification of Benedict–Webb–Rubin (SBWR) EoS, the Critical Point-based Revised Perturbed-Chain Association Fluid Theory (CP-PC-SAFT) EoS, and the Conductor-like Screening Model for Real Solvents (COSMO-RS). It has been demonstrated that the three EoS under consideration yield similar and qualitatively accurate predictions of VLE, which is not the case for the COSMO-RS model examined. Although CP-PC-SAFT EoS exhibits only minor superiority in comparison with PR and SBWR EoS in predicting VLE in the system under consideration, its relative complexity can be justified when taking into account the entire thermodynamic phase space and, in particular, considering the liquid densities and sound velocities over a wider pressure-volume-temperature range.

14C as a tool to trace terrestrial carbon in a complex lake system: implications for foodweb structure and carbon cycling

Carbon and nitrogen stable isotope analysis (SIA) has identified the terrestrial subsidy of freshwater food-webs but relies on different 13C fractionation in aquatic and terrestrial primary producers. However dissolved inorganic carbon (DIC) is partly comprised of 13C depleted respiration of terrestrial C and ‘old’ C derived from weathering of catchment geology. SIA thus fails to differentiate between the contribution of old and recently fixed terrestrial C. DIC in alkaline lakes is partially derived from weathering of 14C-free carbonaceous bedrock This
yields an artificial age offset leading samples to appear significantly older than their actual age. As such, 14C can be used as a biomarker to identify the proportion of autochthonous C in the food-web. With terrestrial C inputs likely to increase, the origin and utilisation of ‘old’ or ‘recent’ allochthonous C in the food-web can also be determined. Stable isotopes and 14C were measured for biota, particulate organic matter (POM), DIC and dissolved organic carbon (DOC) from Lough Erne, Northern Ireland, a humic but alkaline lake. High winter δ15N values in calanoid zooplankton (δ15N =24‰) relative to phytoplankton and POM (δ15N =6‰ and 12‰ respectively) may reflect several microbial trophic levels between terrestrial C and calanoids. Furthermore winter calanoid 14C ages are consistent with DOC from inflowing rivers (87 and 75 years BP respectively) but not phytoplankton (355 years BP). Summer calanoid δ13N, δ15N and 14C (312 years BP) indicate greater reliance on phytoplankton. There is also temporal and spatial variation in DIC, DOC and POM C isotopes.

The effect of probe interval estimation on attack detection performance of a WLAN independent intrusion detection system

A new niche of densely populated, unprotected networks is becoming more prevalent in public areas such as Shopping Malls, defined here as independent open-access networks, which have attributes that make attack detection more challenging than in typical enterprise networks. To address these challenges, new detection systems which do not rely on knowledge of internal device state are investigated here. This paper shows that this lack of state information requires an additional metric (The exchange timeout window) for detection of WLAN Denial of Service Probe Flood attacks. Variability in this metric has a significant influence on the ability of a detection system to reliably detect the presence of attacks. A parameter selection method is proposed which is shown to provide reliability and repeatability in attack detection in WLANs. Results obtained from ongoing live trials are presented that demonstrate the importance of accurately estimating probe request and probe response timeouts in future Independent Intrusion Detection Systems.

14C as a tool to trace terrestrial carbon in a complex lake system: implications for food-web structure and carbon cycling

Globally lakes bury and remineralise significant quantities of terrestrial C, and the associated flux of terrestrial C strongly influences their functioning. Changing deposition chemistry, land use and climate induced impacts on hydrology will affect soil biogeochemistry and terrestrial C export¹ and hence lake ecology with potential feedbacks for regional and global C cycling. C and nitrogen stable isotope analysis (SIA) has identified the terrestrial subsidy of freshwater food webs. The approach relies on different ¹³C fractionation in aquatic and terrestrial primary producers, but also that inorganic C demands of aquatic primary producers are partly met by ¹³C depleted C from respiration of terrestrial C, and ‘old’ C derived from weathering of catchment geology. SIA thus fails to differentiate between the contributions of old and recently fixed terrestrial C. Natural abundance ¹⁴C can be used as an additional biomarker to untangle riverine food webs² where aquatic and terrestrial δ ¹³C overlap, but may also be valuable for examining the age and origin of C in the lake. Primary production in lakes is based on dissolved inorganic C (DIC). DIC in alkaline lakes is partially derived from weathering of carbonaceous bedrock, a proportion of which is¹⁴C-free. The low ¹⁴C activity yields an artificial age offset leading samples to appear hundreds to thousands of years older than their actual age. As such, ¹⁴C can be used to identify the proportion of autochthonous C in the food-web. With terrestrial C inputs likely to increase, the origin and utilisation of ‘fossil’ or ‘recent’ allochthonous C in the food-web can also be determined. Stable isotopes and 14C were measured for biota, particulate organic matter (POM), DIC and dissolved organic carbon (DOC) from Lough Erne, Northern Ireland, a humic alkaline lake. Temporal and spatial variation was evident in DIC, DOC and POM C isotopes with implications for the fluctuation in terrestrial export processes. Ramped pyrolysis of lake surface sediment indicates the burial of two C components. ¹⁴C activity (507 ± 30 BP) of sediment combusted at 400˚C was consistent with algal values and younger than bulk sediment values (1097 ± 30 BP). The sample was subsequently combusted at 850˚C, yielding 14C values (1471 ± 30 BP) older than the bulk sediment age, suggesting that fossil terrestrial carbon is also buried in the sediment. Stable isotopes in the food web indicate that terrestrial organic C is also utilised by lake organisms. High winter δ ¹⁵N values in calanoid zooplankton (δ ¹⁵N = 24%¸) relative to phytoplankton and POM (δ ¹⁵N = 6h and 12h respectively) may reflect several microbial trophic levels between terrestrial C and calanoids. Furthermore winter calanoid 14C ages are consistent with DOC from an inflowing river (75 ± 24 BP), not phytoplankton (367 ± 70 BP). Summer calanoid δ ^13C, δ ¹⁵N and ¹⁴C (345 ± 80 BP) indicate greater reliance on phytoplankton.

¹ Monteith, D.T et al., (2007) Dissolved organic carbon trends resulting from changes in atmospheric deposition chemistry. Nature, 450:537-535

² Caraco, N., et al.,(2010) Millennial-aged organic carbon subsidies to a modern river food web. Ecology,91: 2385-2393.

The Fate of Terrestrial Carbon in a Complex Lake System: Lough Erne

Lake food webs were in the past viewed as being fuelled solely by primary production – i.e. by photosynthetic plants and algae. However this has changed as the exports of terrestrial areas into lakes have been taken into account. Previously, terrestrial carbon in lakes was thought to have been buried in sediments or exported to the atmosphere, however recent studies have indicated that terrestrial carbon can supplement primary production in some lakes, or in others be the dominant source of production for the lake food web. In this study radiocarbon has been used in conjunction with stable carbon and nitrogen isotopes to show the utilisation of terrestrial carbon in the food web. The fate of terrestrial carbon in the lake will be discussed as well as the possible mechanisms for the transfer of terrestrial carbon for utilisation in the lake.

HpMC: An Energy- Aware Management System for Multi-Level Memory Architectures

DRAM technology faces density and power challenges to increase capacity because of limitations of physical cell design. To overcome these limitations, system designers are exploring alternative solutions that combine DRAM and emerging NVRAM technologies. Previous work on heterogeneous memories focuses, mainly, on two system designs: PCache, a hierarchical, inclusive memory system, and HRank, a flat, non-inclusive memory system. We demonstrate that neither of these designs can universally achieve high performance and energy efficiency across a suite of HPC workloads. In this work, we investigate the impact of a number of multilevel memory designs on the performance, power, and energy consumption of applications. To achieve this goal and overcome the limited number of available tools to study heterogeneous memories, we created HMsim, an infrastructure that enables n-level, heterogeneous memory studies by leveraging existing memory simulators. We, then, propose HpMC, a new memory controller design that combines the best aspects of existing management policies to improve performance and energy. Our energy-aware memory management system dynamically switches between PCache and HRank based on the temporal locality of applications. Our results show that HpMC reduces energy consumption from 13% to 45% compared to PCache and HRank, while providing the same bandwidth and higher capacity than a conventional DRAM system.

Search for a New International System

The crisis in Ukraine has three separate but closely linked causes, which must be understood before any long-term solution is found. The three causes are unstable post-Soviet borders, Ukrainian difficulties in state- and nation- building, and Russia’s frustration with the post-Cold War status quo, believes Dr Alexander Titov, who insists that the search for a new international system is taking shape through this current crisis in Europe

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

Reserve from wind power potential in system economic loading

The growth of wind power in some power systems is hampered by the system requirement for emergency reserve to cover loss of the biggest infeed. The study demonstrates that reserve provision from the wind sector itself has economic and operational benefits. A heuristic algorithm has been developed that can model the relevant aspects of emergency reserve provision in a system with both thermal and wind generations. The proposed algorithm is first validated by comparing its performance with established economic scheduling methods applied to a representative power system. The algorithm is then used to demonstrate the economic benefit of reserve provision from the wind sector. It is shown that such provision reduces wind energy curtailment and thermal unit ramping. Finally, it is shown that a wind sector capable of providing emergency reserve can expand economically beyond the capacity limit that would otherwise apply.

Hierarchical energy management system for multi-source multi-product microgrids

This paper proposes a hierarchical energy management system for multi-source multi-product (MSMP) microgrids. Traditional energy hub based scheduling method is combined with a hierarchical control structure to incorporate transient characteristics of natural gas flow and dynamics of energy converters in microgrids. The hierarchical EMS includes a supervisory control layer, an optimizing control layer, and an execution control layer. In order to efficiently accommodate the systems multi time-scale characteristics, the optimizing control layer is decomposed into three sub-layers: slow, medium and fast. Thermal, gas and electrical management systems are integrated into the slow, medium, and fast control layer, respectively. Compared with wind energy, solar energy is easier to integrate and more suitable for the microgrid environment, therefore, potential impacts of the hierarchical EMS on MSMP microgrids is investigated based on a building energy system integrating photovoltaic and microturbines. Numerical studies indicate that by using a hierarchical EMS, MSMP microgrids can be economically operated. Also, interactions among thermal, gas, and electrical system can be effectively managed.

Dynamic Modeling and Interaction of Hybrid Natural Gas and Electricity Supply System in Microgrid

Natural gas (NG) network and electric network are becoming tightly integrated by microturbines in the microgrid. Interactions between these two networks are not well captured by the traditional microturbine (MT) models. To address this issue, two improved models for single-shaft MT and split-shaft MT are proposed in this paper. In addition, dynamic models of the hybrid natural gas and electricity system (HGES) are developed for the analysis of their interactions. Dynamic behaviors of natural gas in pipes are described by partial differential equations (PDEs), while the electric network is described by differential algebraic equations (DAEs). So the overall network is a typical two-time scale dynamic system. Numerical studies indicate that the two-time scale algorithm is faster and can capture the interactions between the two networks. The results also show the HGES with a single-shaft MT is a weakly coupled system in which disturbances in the two networks mainly influence the dc link voltage of the MT, while the split-shaft MT is a strongly coupled system where the impact of an event will affect both networks.

A Continuous Time Markov Chain Based Sequential Analytical Approach for Composite Power System Reliability Assessment

This paper proposes a continuous time Markov chain (CTMC) based sequential analytical approach for composite generation and transmission systems reliability assessment. The basic idea is to construct a CTMC model for the composite system. Based on this model, sequential analyses are performed. Various kinds of reliability indices can be obtained, including expectation, variance, frequency, duration and probability distribution. In order to reduce the dimension of the state space, traditional CTMC modeling approach is modified by merging all high order contingencies into a single state, which can be calculated by Monte Carlo simulation (MCS). Then a state mergence technique is developed to integrate all normal states to further reduce the dimension of the CTMC model. Moreover, a time discretization method is presented for the CTMC model calculation. Case studies are performed on the RBTS and a modified IEEE 300-bus test system. The results indicate that sequential reliability assessment can be performed by the proposed approach. Comparing with the traditional sequential Monte Carlo simulation method, the proposed method is more efficient, especially in small scale or very reliable power systems.